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base on π A ranked list of awesome machine learning Python libraries. Updated weekly. <!-- markdownlint-disable -->
<h1 align="center">
Best-of Machine Learning with Python
<br>
</h1>
<p align="center">
<strong>π A ranked list of awesome machine learning Python libraries. Updated weekly.</strong>
</p>
<p align="center">
<a href="https://github.com/ml-tooling/best-of" title="Best-of-badge"><img src="http://bit.ly/3o3EHNN"></a>
<a href="#Contents" title="Project Count"><img src="https://img.shields.io/badge/projects-920-blue.svg?color=5ac4bf"></a>
<a href="#Contribution" title="Contributions are welcome"><img src="https://img.shields.io/badge/contributions-welcome-green.svg"></a>
<a href="https://github.com/ml-tooling/best-of-ml-python/releases" title="Best-of Updates"><img src="https://img.shields.io/github/release-date/ml-tooling/best-of-ml-python?color=green&label=updated"></a>
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This curated list contains 920 awesome open-source projects with a total of 4.7M stars grouped into 34 categories. All projects are ranked by a project-quality score, which is calculated based on various metrics automatically collected from GitHub and different package managers. If you like to add or update projects, feel free to open an [issue](https://github.com/ml-tooling/best-of-ml-python/issues/new/choose), submit a [pull request](https://github.com/ml-tooling/best-of-ml-python/pulls), or directly edit the [projects.yaml](https://github.com/ml-tooling/best-of-ml-python/edit/main/projects.yaml). Contributions are very welcome!
---
<p align="center">
π§ββοΈ Discover other <a href="https://best-of.org">best-of lists</a> or create <a href="https://github.com/best-of-lists/best-of/blob/main/create-best-of-list.md">your own</a>.<br>
π« Subscribe to our <a href="https://mltooling.substack.com/subscribe">newsletter</a> for updates and trending projects.
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---
## Contents
- [Machine Learning Frameworks](#machine-learning-frameworks) _63 projects_
- [Data Visualization](#data-visualization) _55 projects_
- [Text Data & NLP](#text-data--nlp) _103 projects_
- [Image Data](#image-data) _64 projects_
- [Graph Data](#graph-data) _36 projects_
- [Audio Data](#audio-data) _29 projects_
- [Geospatial Data](#geospatial-data) _22 projects_
- [Financial Data](#financial-data) _25 projects_
- [Time Series Data](#time-series-data) _29 projects_
- [Medical Data](#medical-data) _19 projects_
- [Tabular Data](#tabular-data) _5 projects_
- [Optical Character Recognition](#optical-character-recognition) _12 projects_
- [Data Containers & Structures](#data-containers--structures) _1 projects_
- [Data Loading & Extraction](#data-loading--extraction) _1 projects_
- [Web Scraping & Crawling](#web-scraping--crawling) _1 projects_
- [Data Pipelines & Streaming](#data-pipelines--streaming) _1 projects_
- [Distributed Machine Learning](#distributed-machine-learning) _36 projects_
- [Hyperparameter Optimization & AutoML](#hyperparameter-optimization--automl) _52 projects_
- [Reinforcement Learning](#reinforcement-learning) _23 projects_
- [Recommender Systems](#recommender-systems) _17 projects_
- [Privacy Machine Learning](#privacy-machine-learning) _7 projects_
- [Workflow & Experiment Tracking](#workflow--experiment-tracking) _40 projects_
- [Model Serialization & Deployment](#model-serialization--deployment) _20 projects_
- [Model Interpretability](#model-interpretability) _54 projects_
- [Vector Similarity Search (ANN)](#vector-similarity-search-ann) _13 projects_
- [Probabilistics & Statistics](#probabilistics--statistics) _24 projects_
- [Adversarial Robustness](#adversarial-robustness) _9 projects_
- [GPU & Accelerator Utilities](#gpu--accelerator-utilities) _20 projects_
- [Tensorflow Utilities](#tensorflow-utilities) _16 projects_
- [Jax Utilities](#jax-utilities) _3 projects_
- [Sklearn Utilities](#sklearn-utilities) _19 projects_
- [Pytorch Utilities](#pytorch-utilities) _32 projects_
- [Database Clients](#database-clients) _1 projects_
- [Others](#others) _66 projects_
## Explanation
- π₯π₯π₯ Combined project-quality score
- βοΈ Star count from GitHub
- π£ New project _(less than 6 months old)_
- π€ Inactive project _(6 months no activity)_
- π Dead project _(12 months no activity)_
- ππ Project is trending up or down
- β Project was recently added
- βοΈ Warning _(e.g. missing/risky license)_
- π¨βπ» Contributors count from GitHub
- π Fork count from GitHub
- π Issue count from GitHub
- β±οΈ Last update timestamp on package manager
- π₯ Download count from package manager
- π¦ Number of dependent projects
- <img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"> Tensorflow related project
- <img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"> Sklearn related project
- <img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"> PyTorch related project
- <img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"> MxNet related project
- <img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"> Apache Spark related project
- <img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"> Jupyter related project
- <img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"> PaddlePaddle related project
- <img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"> Pandas related project
- <img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"> Jax related project
<br>
## Machine Learning Frameworks
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_General-purpose machine learning and deep learning frameworks._
<details><summary><b><a href="https://github.com/tensorflow/tensorflow">Tensorflow</a></b> (π₯57 Β· β 190K Β· π) - An Open Source Machine Learning Framework for Everyone. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/tensorflow) (π¨βπ» 4.7K Β· π 74K Β· π¦ 440K Β· π 45K - 13% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/tensorflow/tensorflow
```
- [PyPi](https://pypi.org/project/tensorflow) (π₯ 24M / month Β· π¦ 8.1K Β· β±οΈ 25.10.2024):
```
pip install tensorflow
```
- [Conda](https://anaconda.org/conda-forge/tensorflow) (π₯ 5.2M Β· β±οΈ 17.10.2024):
```
conda install -c conda-forge tensorflow
```
- [Docker Hub](https://hub.docker.com/r/tensorflow/tensorflow) (π₯ 79M Β· β 2.6K Β· β±οΈ 16.12.2024):
```
docker pull tensorflow/tensorflow
```
</details>
<details><summary><b><a href="https://github.com/pytorch/pytorch">PyTorch</a></b> (π₯55 Β· β 85K) - Tensors and Dynamic neural networks in Python with strong GPU.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pytorch/pytorch) (π¨βπ» 5.3K Β· π 23K Β· π₯ 69K Β· π¦ 600K Β· π 49K - 32% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/pytorch/pytorch
```
- [PyPi](https://pypi.org/project/torch) (π₯ 34M / month Β· π¦ 20K Β· β±οΈ 29.10.2024):
```
pip install torch
```
- [Conda](https://anaconda.org/pytorch/pytorch) (π₯ 25M Β· β±οΈ 28.10.2024):
```
conda install -c pytorch pytorch
```
</details>
<details><summary><b><a href="https://github.com/scikit-learn/scikit-learn">scikit-learn</a></b> (π₯53 Β· β 61K) - scikit-learn: machine learning in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/scikit-learn/scikit-learn) (π¨βπ» 3.2K Β· π 25K Β· π₯ 1K Β· π¦ 990K Β· π 12K - 17% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/scikit-learn/scikit-learn
```
- [PyPi](https://pypi.org/project/scikit-learn) (π₯ 81M / month Β· π¦ 26K Β· β±οΈ 09.12.2024):
```
pip install scikit-learn
```
- [Conda](https://anaconda.org/conda-forge/scikit-learn) (π₯ 33M Β· β±οΈ 09.12.2024):
```
conda install -c conda-forge scikit-learn
```
</details>
<details><summary><b><a href="https://github.com/keras-team/keras">Keras</a></b> (π₯48 Β· β 62K) - Deep Learning for humans. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/keras-team/keras) (π¨βπ» 1.4K Β· π 19K Β· π 12K - 2% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/keras-team/keras
```
- [PyPi](https://pypi.org/project/keras) (π₯ 15M / month Β· π¦ 1.7K Β· β±οΈ 26.11.2024):
```
pip install keras
```
- [Conda](https://anaconda.org/conda-forge/keras) (π₯ 3.9M Β· β±οΈ 10.12.2024):
```
conda install -c conda-forge keras
```
</details>
<details><summary><b><a href="https://github.com/jax-ml/jax">jax</a></b> (π₯46 Β· β 31K Β· π) - Composable transformations of Python+NumPy programs: differentiate,.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/jax-ml/jax) (π¨βπ» 810 Β· π 2.8K Β· π¦ 34K Β· π 5.8K - 25% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/google/jax
```
- [PyPi](https://pypi.org/project/jax) (π₯ 4.8M / month Β· π¦ 2.1K Β· β±οΈ 17.12.2024):
```
pip install jax
```
- [Conda](https://anaconda.org/conda-forge/jaxlib) (π₯ 2M Β· β±οΈ 12.12.2024):
```
conda install -c conda-forge jaxlib
```
</details>
<details><summary><b><a href="https://github.com/dmlc/xgboost">XGBoost</a></b> (π₯46 Β· β 26K) - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/dmlc/xgboost) (π¨βπ» 660 Β· π 8.7K Β· π₯ 13K Β· π¦ 120K Β· π 5.4K - 8% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/dmlc/xgboost
```
- [PyPi](https://pypi.org/project/xgboost) (π₯ 26M / month Β· π¦ 2.1K Β· β±οΈ 26.11.2024):
```
pip install xgboost
```
- [Conda](https://anaconda.org/conda-forge/xgboost) (π₯ 5.6M Β· β±οΈ 03.12.2024):
```
conda install -c conda-forge xgboost
```
</details>
<details><summary><b><a href="https://github.com/PaddlePaddle/Paddle">PaddlePaddle</a></b> (π₯45 Β· β 22K) - PArallel Distributed Deep LEarning: Machine Learning.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/PaddlePaddle/Paddle) (π¨βπ» 1.3K Β· π 5.6K Β· π₯ 15K Β· π¦ 6.6K Β· π 19K - 9% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/PaddlePaddle/Paddle
```
- [PyPi](https://pypi.org/project/paddlepaddle) (π₯ 340K / month Β· π¦ 190 Β· β±οΈ 01.11.2024):
```
pip install paddlepaddle
```
</details>
<details><summary><b><a href="https://github.com/statsmodels/statsmodels">StatsModels</a></b> (π₯45 Β· β 10K) - Statsmodels: statistical modeling and econometrics in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/statsmodels/statsmodels) (π¨βπ» 450 Β· π 3.1K Β· π₯ 35 Β· π¦ 150K Β· π 5.7K - 50% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/statsmodels/statsmodels
```
- [PyPi](https://pypi.org/project/statsmodels) (π₯ 16M / month Β· π¦ 4.5K Β· β±οΈ 03.10.2024):
```
pip install statsmodels
```
- [Conda](https://anaconda.org/conda-forge/statsmodels) (π₯ 16M Β· β±οΈ 03.10.2024):
```
conda install -c conda-forge statsmodels
```
</details>
<details><summary><b><a href="https://github.com/apache/spark">PySpark</a></b> (π₯44 Β· β 40K) - Apache Spark Python API. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/apache/spark) (π¨βπ» 3.2K Β· π 28K Β· β±οΈ 19.12.2024):
```
git clone https://github.com/apache/spark
```
- [PyPi](https://pypi.org/project/pyspark) (π₯ 31M / month Β· π¦ 1.6K Β· β±οΈ 25.10.2024):
```
pip install pyspark
```
- [Conda](https://anaconda.org/conda-forge/pyspark) (π₯ 3.6M Β· β±οΈ 16.12.2024):
```
conda install -c conda-forge pyspark
```
</details>
<details><summary><b><a href="https://github.com/Lightning-AI/pytorch-lightning">pytorch-lightning</a></b> (π₯44 Β· β 29K) - Pretrain, finetune ANY AI model of ANY size on.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/Lightning-AI/pytorch-lightning) (π¨βπ» 990 Β· π 3.4K Β· π₯ 11K Β· π¦ 40K Β· π 7.2K - 11% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/Lightning-AI/lightning
```
- [PyPi](https://pypi.org/project/pytorch-lightning) (π₯ 6.8M / month Β· π¦ 1.5K Β· β±οΈ 17.12.2024):
```
pip install pytorch-lightning
```
- [Conda](https://anaconda.org/conda-forge/pytorch-lightning) (π₯ 1.4M Β· β±οΈ 13.12.2024):
```
conda install -c conda-forge pytorch-lightning
```
</details>
<details><summary><b><a href="https://github.com/microsoft/LightGBM">LightGBM</a></b> (π₯43 Β· β 17K) - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/microsoft/LightGBM) (π¨βπ» 320 Β· π 3.8K Β· π₯ 240K Β· π¦ 42K Β· π 3.5K - 10% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/microsoft/LightGBM
```
- [PyPi](https://pypi.org/project/lightgbm) (π₯ 11M / month Β· π¦ 1.1K Β· β±οΈ 26.07.2024):
```
pip install lightgbm
```
- [Conda](https://anaconda.org/conda-forge/lightgbm) (π₯ 2.9M Β· β±οΈ 10.10.2024):
```
conda install -c conda-forge lightgbm
```
</details>
<details><summary><b><a href="https://github.com/catboost/catboost">Catboost</a></b> (π₯42 Β· β 8.2K) - A fast, scalable, high performance Gradient Boosting on Decision.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/catboost/catboost) (π¨βπ» 1.3K Β· π 1.2K Β· π₯ 330K Β· π¦ 16 Β· π 2.4K - 24% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/catboost/catboost
```
- [PyPi](https://pypi.org/project/catboost) (π₯ 3.6M / month Β· π¦ 540 Β· β±οΈ 07.09.2024):
```
pip install catboost
```
- [Conda](https://anaconda.org/conda-forge/catboost) (π₯ 1.8M Β· β±οΈ 07.09.2024):
```
conda install -c conda-forge catboost
```
</details>
<details><summary><b><a href="https://github.com/fastai/fastai">Fastai</a></b> (π₯41 Β· β 26K) - The fastai deep learning library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/fastai/fastai) (π¨βπ» 670 Β· π 7.6K Β· π¦ 20K Β· π 1.8K - 12% open Β· β±οΈ 14.12.2024):
```
git clone https://github.com/fastai/fastai
```
- [PyPi](https://pypi.org/project/fastai) (π₯ 520K / month Β· π¦ 310 Β· β±οΈ 19.10.2024):
```
pip install fastai
```
</details>
<details><summary><b><a href="https://github.com/apache/flink">PyFlink</a></b> (π₯40 Β· β 24K Β· π) - Apache Flink Python API. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/apache/flink) (π¨βπ» 2K Β· π 13K Β· π¦ 21 Β· β±οΈ 19.12.2024):
```
git clone https://github.com/apache/flink
```
- [PyPi](https://pypi.org/project/apache-flink) (π₯ 32M / month Β· π¦ 35 Β· β±οΈ 01.08.2024):
```
pip install apache-flink
```
</details>
<details><summary><b><a href="https://github.com/google/flax">Flax</a></b> (π₯38 Β· β 6.2K) - Flax is a neural network library for JAX that is designed for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/google/flax) (π¨βπ» 250 Β· π 650 Β· π₯ 58 Β· π¦ 11K Β· π 1.1K - 29% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/google/flax
```
- [PyPi](https://pypi.org/project/flax) (π₯ 940K / month Β· π¦ 490 Β· β±οΈ 19.11.2024):
```
pip install flax
```
- [Conda](https://anaconda.org/conda-forge/flax) (π₯ 82K Β· β±οΈ 20.11.2024):
```
conda install -c conda-forge flax
```
</details>
<details><summary><b><a href="https://github.com/Theano/Theano">Theano</a></b> (π₯37 Β· β 9.9K Β· π€) - Theano was a Python library that allows you to define, optimize, and.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/Theano/Theano) (π¨βπ» 390 Β· π 2.5K Β· π¦ 16K Β· π 2.8K - 25% open Β· β±οΈ 15.01.2024):
```
git clone https://github.com/Theano/Theano
```
- [PyPi](https://pypi.org/project/theano) (π₯ 90K / month Β· π¦ 170 Β· β±οΈ 27.07.2020):
```
pip install theano
```
- [Conda](https://anaconda.org/conda-forge/theano) (π₯ 2.5M Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge theano
```
</details>
<details><summary><b><a href="https://github.com/jina-ai/serve">Jina</a></b> (π₯36 Β· β 21K Β· π) - Build multimodal AI applications with cloud-native stack. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/jina-ai/serve) (π¨βπ» 180 Β· π 2.2K Β· π 1.9K - 0% open Β· β±οΈ 12.11.2024):
```
git clone https://github.com/jina-ai/jina
```
- [PyPi](https://pypi.org/project/jina) (π₯ 76K / month Β· π¦ 27 Β· β±οΈ 08.11.2024):
```
pip install jina
```
- [Conda](https://anaconda.org/conda-forge/jina-core) (π₯ 82K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge jina-core
```
- [Docker Hub](https://hub.docker.com/r/jinaai/jina) (π₯ 1.8M Β· β 8 Β· β±οΈ 12.11.2024):
```
docker pull jinaai/jina
```
</details>
<details><summary><b><a href="https://github.com/arogozhnikov/einops">einops</a></b> (π₯35 Β· β 8.6K Β· π) - Flexible and powerful tensor operations for readable and reliable code.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/arogozhnikov/einops) (π¨βπ» 32 Β· π 350 Β· π¦ 55K Β· π 180 - 17% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/arogozhnikov/einops
```
- [PyPi](https://pypi.org/project/einops) (π₯ 5.4M / month Β· π¦ 2K Β· β±οΈ 28.04.2024):
```
pip install einops
```
- [Conda](https://anaconda.org/conda-forge/einops) (π₯ 310K Β· β±οΈ 15.12.2024):
```
conda install -c conda-forge einops
```
</details>
<details><summary><b><a href="https://github.com/VowpalWabbit/vowpal_wabbit">Vowpal Wabbit</a></b> (π₯35 Β· β 8.5K) - Vowpal Wabbit is a machine learning system which pushes the.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/VowpalWabbit/vowpal_wabbit) (π¨βπ» 340 Β· π 1.9K Β· π¦ 1 Β· π 1.3K - 10% open Β· β±οΈ 01.08.2024):
```
git clone https://github.com/VowpalWabbit/vowpal_wabbit
```
- [PyPi](https://pypi.org/project/vowpalwabbit) (π₯ 120K / month Β· π¦ 40 Β· β±οΈ 08.08.2024):
```
pip install vowpalwabbit
```
- [Conda](https://anaconda.org/conda-forge/vowpalwabbit) (π₯ 260K Β· β±οΈ 27.11.2024):
```
conda install -c conda-forge vowpalwabbit
```
</details>
<details><summary><b><a href="https://github.com/mlpack/mlpack">mlpack</a></b> (π₯35 Β· β 5.2K) - mlpack: a fast, header-only C++ machine learning library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/mlpack/mlpack) (π¨βπ» 330 Β· π 1.6K Β· π 1.6K - 1% open Β· β±οΈ 13.12.2024):
```
git clone https://github.com/mlpack/mlpack
```
- [PyPi](https://pypi.org/project/mlpack) (π₯ 6K / month Β· π¦ 6 Β· β±οΈ 11.12.2024):
```
pip install mlpack
```
- [Conda](https://anaconda.org/conda-forge/mlpack) (π₯ 280K Β· β±οΈ 22.09.2024):
```
conda install -c conda-forge mlpack
```
</details>
<details><summary><b><a href="https://github.com/pytorch/ignite">Ignite</a></b> (π₯35 Β· β 4.6K) - High-level library to help with training and evaluating neural.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pytorch/ignite) (π¨βπ» 720 Β· π 620 Β· π¦ 3.4K Β· π 1.4K - 11% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/pytorch/ignite
```
- [PyPi](https://pypi.org/project/pytorch-ignite) (π₯ 140K / month Β· π¦ 100 Β· β±οΈ 19.12.2024):
```
pip install pytorch-ignite
```
- [Conda](https://anaconda.org/pytorch/ignite) (π₯ 210K Β· β±οΈ 13.08.2024):
```
conda install -c pytorch ignite
```
</details>
<details><summary><b><a href="https://github.com/explosion/thinc">Thinc</a></b> (π₯35 Β· β 2.8K) - A refreshing functional take on deep learning, compatible with your favorite.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/explosion/thinc) (π¨βπ» 66 Β· π 280 Β· π₯ 520 Β· π¦ 58K Β· π 150 - 14% open Β· β±οΈ 11.12.2024):
```
git clone https://github.com/explosion/thinc
```
- [PyPi](https://pypi.org/project/thinc) (π₯ 13M / month Β· π¦ 150 Β· β±οΈ 16.12.2024):
```
pip install thinc
```
- [Conda](https://anaconda.org/conda-forge/thinc) (π₯ 3.2M Β· β±οΈ 03.12.2024):
```
conda install -c conda-forge thinc
```
</details>
<details><summary><b><a href="https://github.com/ludwig-ai/ludwig">Ludwig</a></b> (π₯33 Β· β 11K) - Low-code framework for building custom LLMs, neural networks, and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/ludwig-ai/ludwig) (π¨βπ» 160 Β· π 1.2K Β· π¦ 290 Β· π 1.1K - 4% open Β· β±οΈ 17.10.2024):
```
git clone https://github.com/ludwig-ai/ludwig
```
- [PyPi](https://pypi.org/project/ludwig) (π₯ 1.9K / month Β· π¦ 6 Β· β±οΈ 30.07.2024):
```
pip install ludwig
```
</details>
<details><summary><b><a href="https://github.com/google-deepmind/dm-haiku">Haiku</a></b> (π₯32 Β· β 2.9K) - JAX-based neural network library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/google-deepmind/dm-haiku) (π¨βπ» 84 Β· π 230 Β· π¦ 2.2K Β· π 250 - 28% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/deepmind/dm-haiku
```
- [PyPi](https://pypi.org/project/dm-haiku) (π₯ 260K / month Β· π¦ 180 Β· β±οΈ 16.10.2024):
```
pip install dm-haiku
```
- [Conda](https://anaconda.org/conda-forge/dm-haiku) (π₯ 26K Β· β±οΈ 23.10.2024):
```
conda install -c conda-forge dm-haiku
```
</details>
<details><summary><b><a href="https://github.com/google-deepmind/sonnet">Sonnet</a></b> (π₯31 Β· β 9.8K) - TensorFlow-based neural network library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/google-deepmind/sonnet) (π¨βπ» 59 Β· π 1.3K Β· π¦ 1.4K Β· π 190 - 16% open Β· β±οΈ 14.11.2024):
```
git clone https://github.com/deepmind/sonnet
```
- [PyPi](https://pypi.org/project/dm-sonnet) (π₯ 19K / month Β· π¦ 19 Β· β±οΈ 02.01.2024):
```
pip install dm-sonnet
```
- [Conda](https://anaconda.org/conda-forge/sonnet) (π₯ 37K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge sonnet
```
</details>
<details><summary><b><a href="https://github.com/skorch-dev/skorch">skorch</a></b> (π₯31 Β· β 5.9K) - A scikit-learn compatible neural network library that wraps.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/skorch-dev/skorch) (π¨βπ» 62 Β· π 390 Β· π¦ 1.5K Β· π 520 - 11% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/skorch-dev/skorch
```
- [PyPi](https://pypi.org/project/skorch) (π₯ 150K / month Β· π¦ 85 Β· β±οΈ 27.05.2024):
```
pip install skorch
```
- [Conda](https://anaconda.org/conda-forge/skorch) (π₯ 790K Β· β±οΈ 30.05.2024):
```
conda install -c conda-forge skorch
```
</details>
<details><summary><b><a href="https://github.com/ROCm/tensorflow-upstream">tensorflow-upstream</a></b> (π₯31 Β· β 690) - TensorFlow ROCm port. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/ROCm/tensorflow-upstream) (π¨βπ» 4.7K Β· π 95 Β· π₯ 26 Β· π 380 - 18% open Β· β±οΈ 06.12.2024):
```
git clone https://github.com/ROCmSoftwarePlatform/tensorflow-upstream
```
- [PyPi](https://pypi.org/project/tensorflow-rocm) (π₯ 6.6K / month Β· π¦ 9 Β· β±οΈ 10.01.2024):
```
pip install tensorflow-rocm
```
</details>
<details><summary><b><a href="https://github.com/determined-ai/determined">Determined</a></b> (π₯30 Β· β 3.1K) - Determined is an open-source machine learning platform.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/determined-ai/determined) (π¨βπ» 120 Β· π 360 Β· π₯ 12K Β· π 450 - 21% open Β· β±οΈ 12.12.2024):
```
git clone https://github.com/determined-ai/determined
```
- [PyPi](https://pypi.org/project/determined) (π₯ 19K / month Β· π¦ 4 Β· β±οΈ 22.11.2024):
```
pip install determined
```
</details>
<details><summary><b><a href="https://github.com/geomstats/geomstats">Geomstats</a></b> (π₯30 Β· β 1.3K) - Computations and statistics on manifolds with geometric structures. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/geomstats/geomstats) (π¨βπ» 93 Β· π 240 Β· π¦ 130 Β· π 570 - 36% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/geomstats/geomstats
```
- [PyPi](https://pypi.org/project/geomstats) (π₯ 3.5K / month Β· π¦ 12 Β· β±οΈ 09.09.2024):
```
pip install geomstats
```
- [Conda](https://anaconda.org/conda-forge/geomstats) (π₯ 4.4K Β· β±οΈ 10.09.2024):
```
conda install -c conda-forge geomstats
```
</details>
<details><summary><b><a href="https://github.com/numenta/nupic-legacy">NuPIC</a></b> (π₯28 Β· β 6.3K) - Numenta Platform for Intelligent Computing is an implementation of.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/numenta/nupic-legacy) (π¨βπ» 120 Β· π 1.6K Β· π₯ 13 Β· π¦ 21 Β· π 1.8K - 25% open Β· β±οΈ 03.12.2024):
```
git clone https://github.com/numenta/nupic
```
- [PyPi](https://pypi.org/project/nupic) (π₯ 2.3K / month Β· β±οΈ 01.09.2016):
```
pip install nupic
```
</details>
<details><summary><b><a href="https://github.com/sony/nnabla">Neural Network Libraries</a></b> (π₯28 Β· β 2.7K) - Neural Network Libraries. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/sony/nnabla) (π¨βπ» 76 Β· π 330 Β· π₯ 1K Β· π 95 - 36% open Β· β±οΈ 15.11.2024):
```
git clone https://github.com/sony/nnabla
```
- [PyPi](https://pypi.org/project/nnabla) (π₯ 10K / month Β· π¦ 44 Β· β±οΈ 29.05.2024):
```
pip install nnabla
```
</details>
<details><summary><b><a href="https://github.com/georgia-tech-db/evadb">EvaDB</a></b> (π₯27 Β· β 2.6K Β· π€) - Database system for AI-powered apps. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/georgia-tech-db/evadb) (π¨βπ» 72 Β· π 260 Β· π₯ 420K Β· π¦ 150 Β· π 300 - 25% open Β· β±οΈ 03.12.2023):
```
git clone https://github.com/georgia-tech-db/eva
```
- [PyPi](https://pypi.org/project/evadb) (π₯ 940 / month Β· β±οΈ 19.11.2023):
```
pip install evadb
```
</details>
<details><summary><b><a href="https://github.com/pyRiemann/pyRiemann">pyRiemann</a></b> (π₯27 Β· β 650) - Machine learning for multivariate data through the Riemannian.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pyRiemann/pyRiemann) (π¨βπ» 36 Β· π 160 Β· π¦ 410 Β· π 110 - 4% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/pyRiemann/pyRiemann
```
- [PyPi](https://pypi.org/project/pyriemann) (π₯ 30K / month Β· π¦ 28 Β· β±οΈ 03.10.2024):
```
pip install pyriemann
```
- [Conda](https://anaconda.org/conda-forge/pyriemann) (π₯ 9.2K Β· β±οΈ 04.10.2024):
```
conda install -c conda-forge pyriemann
```
</details>
<details><summary><b><a href="https://github.com/towhee-io/towhee">Towhee</a></b> (π₯26 Β· β 3.3K) - Towhee is a framework that is dedicated to making neural data.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/towhee-io/towhee) (π¨βπ» 38 Β· π 250 Β· π₯ 2.7K Β· π 670 - 0% open Β· β±οΈ 18.10.2024):
```
git clone https://github.com/towhee-io/towhee
```
- [PyPi](https://pypi.org/project/towhee) (π₯ 16K / month Β· β±οΈ 04.12.2023):
```
pip install towhee
```
</details>
<details><summary><b><a href="https://github.com/shogun-toolbox/shogun">SHOGUN</a></b> (π₯26 Β· β 3K Β· π€) - Unified and efficient Machine Learning. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/shogun-toolbox/shogun) (π¨βπ» 250 Β· π 1K Β· π 1.5K - 27% open Β· β±οΈ 19.12.2023):
```
git clone https://github.com/shogun-toolbox/shogun
```
- [Conda](https://anaconda.org/conda-forge/shogun) (π₯ 150K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge shogun
```
- [Docker Hub](https://hub.docker.com/r/shogun/shogun) (π₯ 1.5K Β· β 1 Β· β±οΈ 31.01.2019):
```
docker pull shogun/shogun
```
</details>
<details><summary><b><a href="https://github.com/amaiya/ktrain">ktrain</a></b> (π₯26 Β· β 1.2K) - ktrain is a Python library that makes deep learning and AI more.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/amaiya/ktrain) (π¨βπ» 17 Β· π 270 Β· π¦ 560 Β· π 500 - 0% open Β· β±οΈ 09.07.2024):
```
git clone https://github.com/amaiya/ktrain
```
- [PyPi](https://pypi.org/project/ktrain) (π₯ 7.5K / month Β· π¦ 4 Β· β±οΈ 19.06.2024):
```
pip install ktrain
```
</details>
<details><summary><b><a href="https://github.com/google/neural-tangents">Neural Tangents</a></b> (π₯24 Β· β 2.3K Β· π€) - Fast and Easy Infinite Neural Networks in Python. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/google/neural-tangents) (π¨βπ» 29 Β· π 240 Β· π₯ 540 Β· π¦ 120 Β· π 160 - 38% open Β· β±οΈ 01.03.2024):
```
git clone https://github.com/google/neural-tangents
```
- [PyPi](https://pypi.org/project/neural-tangents) (π₯ 3K / month Β· π¦ 1 Β· β±οΈ 11.12.2023):
```
pip install neural-tangents
```
</details>
<details><summary><b><a href="https://github.com/nubank/fklearn">fklearn</a></b> (π₯24 Β· β 1.5K) - fklearn: Functional Machine Learning. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/nubank/fklearn) (π¨βπ» 56 Β· π 160 Β· π¦ 16 Β· π 65 - 61% open Β· β±οΈ 14.08.2024):
```
git clone https://github.com/nubank/fklearn
```
- [PyPi](https://pypi.org/project/fklearn) (π₯ 2K / month Β· β±οΈ 14.08.2024):
```
pip install fklearn
```
</details>
<details><summary><b><a href="https://github.com/run-house/runhouse">Runhouse</a></b> (π₯24 Β· β 990) - Dispatch and distribute your ML training to serverless clusters in.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/run-house/runhouse) (π¨βπ» 15 Β· π 35 Β· π₯ 67 Β· π 51 - 17% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/run-house/runhouse
```
- [PyPi](https://pypi.org/project/runhouse) (π₯ 35K / month Β· π¦ 1 Β· β±οΈ 12.12.2024):
```
pip install runhouse
```
</details>
<details><summary><b><a href="https://github.com/Xtra-Computing/thundersvm">ThunderSVM</a></b> (π₯22 Β· β 1.6K Β· π€) - ThunderSVM: A Fast SVM Library on GPUs and CPUs. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/Xtra-Computing/thundersvm) (π¨βπ» 37 Β· π 220 Β· π₯ 2.9K Β· π 230 - 35% open Β· β±οΈ 01.04.2024):
```
git clone https://github.com/Xtra-Computing/thundersvm
```
- [PyPi](https://pypi.org/project/thundersvm) (π₯ 1.9K / month Β· β±οΈ 13.03.2020):
```
pip install thundersvm
```
</details>
<details><summary><b><a href="https://github.com/serengil/chefboost">chefboost</a></b> (π₯22 Β· β 460) - A Lightweight Decision Tree Framework supporting regular algorithms:.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/serengil/chefboost) (π¨βπ» 7 Β· π 100 Β· π¦ 64 Β· β±οΈ 30.10.2024):
```
git clone https://github.com/serengil/chefboost
```
- [PyPi](https://pypi.org/project/chefboost) (π₯ 6.2K / month Β· β±οΈ 30.10.2024):
```
pip install chefboost
```
</details>
<details><summary><b><a href="https://github.com/XiaoMi/mace">mace</a></b> (π₯21 Β· β 5K Β· π€) - MACE is a deep learning inference framework optimized for mobile.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/XiaoMi/mace) (π¨βπ» 69 Β· π 820 Β· π₯ 1.5K Β· π 680 - 8% open Β· β±οΈ 11.03.2024):
```
git clone https://github.com/XiaoMi/mace
```
</details>
<details><summary><b><a href="https://github.com/google/objax">Objax</a></b> (π₯21 Β· β 770 Β· π€) - Objax is a machine learning framework that provides an Object.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/google/objax) (π¨βπ» 26 Β· π 78 Β· π¦ 63 Β· π 110 - 45% open Β· β±οΈ 27.01.2024):
```
git clone https://github.com/google/objax
```
- [PyPi](https://pypi.org/project/objax) (π₯ 740 / month Β· π¦ 4 Β· β±οΈ 06.11.2023):
```
pip install objax
```
</details>
<details><summary><b><a href="https://github.com/pytorchbearer/torchbearer">Torchbearer</a></b> (π₯21 Β· β 640 Β· π€) - torchbearer: A model fitting library for PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pytorchbearer/torchbearer) (π¨βπ» 14 Β· π 68 Β· π¦ 94 Β· π 250 - 4% open Β· β±οΈ 04.12.2023):
```
git clone https://github.com/pytorchbearer/torchbearer
```
- [PyPi](https://pypi.org/project/torchbearer) (π₯ 480 / month Β· π¦ 4 Β· β±οΈ 01.12.2023):
```
pip install torchbearer
```
</details>
<details><summary><b><a href="https://github.com/neoml-lib/neoml">NeoML</a></b> (π₯19 Β· β 770) - Machine learning framework for both deep learning and traditional.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/neoml-lib/neoml) (π¨βπ» 40 Β· π 130 Β· π¦ 2 Β· π 91 - 40% open Β· β±οΈ 30.09.2024):
```
git clone https://github.com/neoml-lib/neoml
```
- [PyPi](https://pypi.org/project/neoml) (π₯ 760 / month Β· β±οΈ 26.12.2023):
```
pip install neoml
```
</details>
<details><summary><b><a href="https://github.com/Xtra-Computing/thundergbm">ThunderGBM</a></b> (π₯19 Β· β 700 Β· π€) - ThunderGBM: Fast GBDTs and Random Forests on GPUs. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/Xtra-Computing/thundergbm) (π¨βπ» 12 Β· π 87 Β· π¦ 4 Β· π 81 - 48% open Β· β±οΈ 29.01.2024):
```
git clone https://github.com/Xtra-Computing/thundergbm
```
- [PyPi](https://pypi.org/project/thundergbm) (π₯ 2K / month Β· β±οΈ 19.09.2022):
```
pip install thundergbm
```
</details>
<details><summary>Show 17 hidden projects...</summary>
- <b><a href="https://github.com/davisking/dlib">dlib</a></b> (π₯40 Β· β 14K) - A toolkit for making real world machine learning and data analysis.. <code><a href="https://tldrlegal.com/search?q=BSL-1.0">βοΈBSL-1.0</a></code>
- <b><a href="https://github.com/apache/mxnet">MXNet</a></b> (π₯38 Β· β 21K Β· π) - Lightweight, Portable, Flexible Distributed/Mobile Deep.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/ivy-llc/ivy">ivy</a></b> (π₯35 Β· β 14K) - Convert Machine Learning Code Between Frameworks. <code><a href="https://tldrlegal.com/search?q=Intel-ACPI">βοΈIntel-ACPI</a></code>
- <b><a href="https://github.com/chainer/chainer">Chainer</a></b> (π₯34 Β· β 5.9K Β· π) - A flexible framework of neural networks for deep learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/mindsdb/mindsdb">MindsDB</a></b> (π₯33 Β· β 27K) - Platform for building AI that can learn and answer.. <code><a href="https://tldrlegal.com/search?q=MulanPSL-1.0">βοΈMulanPSL-1.0</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/apple/turicreate">Turi Create</a></b> (π₯32 Β· β 11K Β· π) - Turi Create simplifies the development of custom machine.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/tensorpack/tensorpack">tensorpack</a></b> (π₯32 Β· β 6.3K Β· π) - A Neural Net Training Interface on TensorFlow, with.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/tflearn/tflearn">TFlearn</a></b> (π₯31 Β· β 9.6K Β· π) - Deep learning library featuring a higher-level API for TensorFlow. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/clab/dynet">dyNET</a></b> (π₯31 Β· β 3.4K Β· π) - DyNet: The Dynamic Neural Network Toolkit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/microsoft/CNTK">CNTK</a></b> (π₯29 Β· β 18K Β· π) - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/Lasagne/Lasagne">Lasagne</a></b> (π₯28 Β· β 3.8K Β· π) - Lightweight library to build and train neural networks in Theano. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/itdxer/neupy">NeuPy</a></b> (π₯25 Β· β 740 Β· π) - NeuPy is a Tensorflow based python library for prototyping and building.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/aksnzhy/xlearn">xLearn</a></b> (π₯24 Β· β 3.1K Β· π) - High performance, easy-to-use, and scalable machine learning (ML).. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/NervanaSystems/neon">neon</a></b> (π₯22 Β· β 3.9K Β· π) - Intel Nervana reference deep learning framework committed to best.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/poets-ai/elegy">elegy</a></b> (π₯19 Β· β 470 Β· π) - A High Level API for Deep Learning in JAX. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/facebookresearch/StarSpace">StarSpace</a></b> (π₯16 Β· β 3.9K Β· π) - Learning embeddings for classification, retrieval and ranking. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/HMUNACHI/nanodl">nanodl</a></b> (π₯15 Β· β 280) - A Jax-based library for designing and training transformer models from.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code>
</details>
<br>
## Data Visualization
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_General-purpose and task-specific data visualization libraries._
<details><summary><b><a href="https://github.com/matplotlib/matplotlib">Matplotlib</a></b> (π₯48 Β· β 20K) - matplotlib: plotting with Python. <code>βUnlicensed</code></summary>
- [GitHub](https://github.com/matplotlib/matplotlib) (π¨βπ» 1.8K Β· π 7.7K Β· π¦ 1.5M Β· π 11K - 14% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/matplotlib/matplotlib
```
- [PyPi](https://pypi.org/project/matplotlib) (π₯ 74M / month Β· π¦ 53K Β· β±οΈ 14.12.2024):
```
pip install matplotlib
```
- [Conda](https://anaconda.org/conda-forge/matplotlib) (π₯ 27M Β· β±οΈ 16.12.2024):
```
conda install -c conda-forge matplotlib
```
</details>
<details><summary><b><a href="https://github.com/plotly/plotly.py">Plotly</a></b> (π₯46 Β· β 16K Β· π) - The interactive graphing library for Python This project now includes.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/plotly/plotly.py) (π¨βπ» 280 Β· π 2.6K Β· π¦ 340K Β· π 3.1K - 18% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/plotly/plotly.py
```
- [PyPi](https://pypi.org/project/plotly) (π₯ 21M / month Β· π¦ 6.3K Β· β±οΈ 12.09.2024):
```
pip install plotly
```
- [Conda](https://anaconda.org/conda-forge/plotly) (π₯ 7.8M Β· β±οΈ 09.12.2024):
```
conda install -c conda-forge plotly
```
- [npm](https://www.npmjs.com/package/plotlywidget) (π₯ 8.8K / month Β· π¦ 9 Β· β±οΈ 12.01.2021):
```
npm install plotlywidget
```
</details>
<details><summary><b><a href="https://github.com/bokeh/bokeh">Bokeh</a></b> (π₯45 Β· β 19K) - Interactive Data Visualization in the browser, from Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/bokeh/bokeh) (π¨βπ» 700 Β· π 4.2K Β· π¦ 96K Β· π 7.8K - 10% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/bokeh/bokeh
```
- [PyPi](https://pypi.org/project/bokeh) (π₯ 4.2M / month Β· π¦ 1.8K Β· β±οΈ 03.12.2024):
```
pip install bokeh
```
- [Conda](https://anaconda.org/conda-forge/bokeh) (π₯ 16M Β· β±οΈ 09.12.2024):
```
conda install -c conda-forge bokeh
```
</details>
<details><summary><b><a href="https://github.com/plotly/dash">dash</a></b> (π₯43 Β· β 22K) - Data Apps & Dashboards for Python. No JavaScript Required. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/plotly/dash) (π¨βπ» 170 Β· π 2.1K Β· π₯ 87 Β· π¦ 74K Β· π 1.9K - 26% open Β· β±οΈ 11.12.2024):
```
git clone https://github.com/plotly/dash
```
- [PyPi](https://pypi.org/project/dash) (π₯ 4.7M / month Β· π¦ 1.3K Β· β±οΈ 04.11.2024):
```
pip install dash
```
- [Conda](https://anaconda.org/conda-forge/dash) (π₯ 1.6M Β· β±οΈ 15.12.2024):
```
conda install -c conda-forge dash
```
</details>
<details><summary><b><a href="https://github.com/vega/altair">Altair</a></b> (π₯43 Β· β 9.5K) - Declarative visualization library for Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/vega/altair) (π¨βπ» 170 Β· π 800 Β· π₯ 220 Β· π¦ 180K Β· π 2K - 9% open Β· β±οΈ 02.12.2024):
```
git clone https://github.com/altair-viz/altair
```
- [PyPi](https://pypi.org/project/altair) (π₯ 25M / month Β· π¦ 920 Β· β±οΈ 23.11.2024):
```
pip install altair
```
- [Conda](https://anaconda.org/conda-forge/altair) (π₯ 2.5M Β· β±οΈ 15.12.2024):
```
conda install -c conda-forge altair
```
</details>
<details><summary><b><a href="https://github.com/mwaskom/seaborn">Seaborn</a></b> (π₯41 Β· β 13K Β· π) - Statistical data visualization in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/mwaskom/seaborn) (π¨βπ» 210 Β· π 1.9K Β· π₯ 460 Β· π¦ 530K Β· π 2.6K - 7% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/mwaskom/seaborn
```
- [PyPi](https://pypi.org/project/seaborn) (π₯ 20M / month Β· π¦ 11K Β· β±οΈ 25.01.2024):
```
pip install seaborn
```
- [Conda](https://anaconda.org/conda-forge/seaborn) (π₯ 11M Β· β±οΈ 09.12.2024):
```
conda install -c conda-forge seaborn
```
</details>
<details><summary><b><a href="https://github.com/pyecharts/pyecharts">pyecharts</a></b> (π₯38 Β· β 15K) - Python Echarts Plotting Library. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pyecharts/pyecharts) (π¨βπ» 45 Β· π 2.9K Β· π₯ 71 Β· π¦ 4.7K Β· π 1.9K - 0% open Β· β±οΈ 03.11.2024):
```
git clone https://github.com/pyecharts/pyecharts
```
- [PyPi](https://pypi.org/project/pyecharts) (π₯ 190K / month Β· π¦ 220 Β· β±οΈ 03.11.2024):
```
pip install pyecharts
```
</details>
<details><summary><b><a href="https://github.com/holoviz/holoviews">HoloViews</a></b> (π₯38 Β· β 2.7K) - With Holoviews, your data visualizes itself. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/holoviz/holoviews) (π¨βπ» 140 Β· π 400 Β· π¦ 13K Β· π 3.4K - 33% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/holoviz/holoviews
```
- [PyPi](https://pypi.org/project/holoviews) (π₯ 440K / month Β· π¦ 400 Β· β±οΈ 11.11.2024):
```
pip install holoviews
```
- [Conda](https://anaconda.org/conda-forge/holoviews) (π₯ 1.9M Β· β±οΈ 13.12.2024):
```
conda install -c conda-forge holoviews
```
- [npm](https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz) (π₯ 200 / month Β· π¦ 5 Β· β±οΈ 01.08.2024):
```
npm install @pyviz/jupyterlab_pyviz
```
</details>
<details><summary><b><a href="https://github.com/ydataai/ydata-profiling">pandas-profiling</a></b> (π₯37 Β· β 13K Β· π) - 1 Line of code data quality profiling & exploratory.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/ydataai/ydata-profiling) (π¨βπ» 130 Β· π 1.7K Β· π₯ 220 Β· π¦ 4.9K Β· π 810 - 28% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/ydataai/pandas-profiling
```
- [PyPi](https://pypi.org/project/pandas-profiling) (π₯ 440K / month Β· π¦ 180 Β· β±οΈ 03.02.2023):
```
pip install pandas-profiling
```
- [Conda](https://anaconda.org/conda-forge/pandas-profiling) (π₯ 480K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge pandas-profiling
```
</details>
<details><summary><b><a href="https://github.com/voxel51/fiftyone">FiftyOne</a></b> (π₯37 Β· β 9K) - Visualize, create, and debug image and video datasets.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/voxel51/fiftyone) (π¨βπ» 140 Β· π 570 Β· π¦ 770 Β· π 1.6K - 31% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/voxel51/fiftyone
```
- [PyPi](https://pypi.org/project/fiftyone) (π₯ 73K / month Β· π¦ 24 Β· β±οΈ 06.12.2024):
```
pip install fiftyone
```
</details>
<details><summary><b><a href="https://github.com/has2k1/plotnine">plotnine</a></b> (π₯37 Β· β 4.1K) - A Grammar of Graphics for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/has2k1/plotnine) (π¨βπ» 110 Β· π 230 Β· π¦ 9.8K Β· π 700 - 11% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/has2k1/plotnine
```
- [PyPi](https://pypi.org/project/plotnine) (π₯ 3.4M / month Β· π¦ 330 Β· β±οΈ 16.12.2024):
```
pip install plotnine
```
- [Conda](https://anaconda.org/conda-forge/plotnine) (π₯ 430K Β· β±οΈ 16.12.2024):
```
conda install -c conda-forge plotnine
```
</details>
<details><summary><b><a href="https://github.com/pyqtgraph/pyqtgraph">PyQtGraph</a></b> (π₯37 Β· β 3.9K) - Fast data visualization and GUI tools for scientific / engineering.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/pyqtgraph/pyqtgraph) (π¨βπ» 300 Β· π 1.1K Β· π¦ 11K Β· π 1.3K - 32% open Β· β±οΈ 06.11.2024):
```
git clone https://github.com/pyqtgraph/pyqtgraph
```
- [PyPi](https://pypi.org/project/pyqtgraph) (π₯ 500K / month Β· π¦ 1K Β· β±οΈ 29.04.2024):
```
pip install pyqtgraph
```
- [Conda](https://anaconda.org/conda-forge/pyqtgraph) (π₯ 630K Β· β±οΈ 11.12.2024):
```
conda install -c conda-forge pyqtgraph
```
</details>
<details><summary><b><a href="https://github.com/pyvista/pyvista">PyVista</a></b> (π₯37 Β· β 2.8K) - 3D plotting and mesh analysis through a streamlined interface for.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pyvista/pyvista) (π¨βπ» 170 Β· π 510 Β· π₯ 840 Β· π¦ 3.8K Β· π 1.8K - 36% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/pyvista/pyvista
```
- [PyPi](https://pypi.org/project/pyvista) (π₯ 400K / month Β· π¦ 580 Β· β±οΈ 27.11.2024):
```
pip install pyvista
```
- [Conda](https://anaconda.org/conda-forge/pyvista) (π₯ 600K Β· β±οΈ 15.12.2024):
```
conda install -c conda-forge pyvista
```
</details>
<details><summary><b><a href="https://github.com/SciTools/cartopy">cartopy</a></b> (π₯36 Β· β 1.4K) - Cartopy - a cartographic python library with matplotlib support. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/SciTools/cartopy) (π¨βπ» 130 Β· π 360 Β· π¦ 6.2K Β· π 1.3K - 23% open Β· β±οΈ 10.12.2024):
```
git clone https://github.com/SciTools/cartopy
```
- [PyPi](https://pypi.org/project/cartopy) (π₯ 410K / month Β· π¦ 720 Β· β±οΈ 08.10.2024):
```
pip install cartopy
```
- [Conda](https://anaconda.org/conda-forge/cartopy) (π₯ 4.3M Β· β±οΈ 07.10.2024):
```
conda install -c conda-forge cartopy
```
</details>
<details><summary><b><a href="https://github.com/lmcinnes/umap">UMAP</a></b> (π₯35 Β· β 7.5K) - Uniform Manifold Approximation and Projection. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/lmcinnes/umap) (π¨βπ» 140 Β· π 810 Β· π¦ 1 Β· π 820 - 58% open Β· β±οΈ 29.11.2024):
```
git clone https://github.com/lmcinnes/umap
```
- [PyPi](https://pypi.org/project/umap-learn) (π₯ 2M / month Β· π¦ 1.1K Β· β±οΈ 28.10.2024):
```
pip install umap-learn
```
- [Conda](https://anaconda.org/conda-forge/umap-learn) (π₯ 2.7M Β· β±οΈ 29.10.2024):
```
conda install -c conda-forge umap-learn
```
</details>
<details><summary><b><a href="https://github.com/xflr6/graphviz">Graphviz</a></b> (π₯35 Β· β 1.7K Β· π€) - Simple Python interface for Graphviz. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/xflr6/graphviz) (π¨βπ» 23 Β· π 210 Β· π¦ 78K Β· π 180 - 6% open Β· β±οΈ 13.05.2024):
```
git clone https://github.com/xflr6/graphviz
```
- [PyPi](https://pypi.org/project/graphviz) (π₯ 18M / month Β· π¦ 2.6K Β· β±οΈ 21.03.2024):
```
pip install graphviz
```
- [Conda](https://anaconda.org/anaconda/python-graphviz) (π₯ 51K Β· β±οΈ 08.04.2024):
```
conda install -c anaconda python-graphviz
```
</details>
<details><summary><b><a href="https://github.com/finos/perspective">Perspective</a></b> (π₯34 Β· β 8.7K) - A data visualization and analytics component, especially.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/finos/perspective) (π¨βπ» 98 Β· π 1.2K Β· π₯ 7.3K Β· π¦ 160 Β· π 840 - 13% open Β· β±οΈ 09.12.2024):
```
git clone https://github.com/finos/perspective
```
- [PyPi](https://pypi.org/project/perspective-python) (π₯ 15K / month Β· π¦ 28 Β· β±οΈ 10.12.2024):
```
pip install perspective-python
```
- [Conda](https://anaconda.org/conda-forge/perspective) (π₯ 1.4M Β· β±οΈ 12.12.2024):
```
conda install -c conda-forge perspective
```
- [npm](https://www.npmjs.com/package/@finos/perspective-jupyterlab) (π₯ 1.9K / month Β· π¦ 6 Β· β±οΈ 10.12.2024):
```
npm install @finos/perspective-jupyterlab
```
</details>
<details><summary><b><a href="https://github.com/holoviz/datashader">datashader</a></b> (π₯34 Β· β 3.3K) - Quickly and accurately render even the largest data. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/holoviz/datashader) (π¨βπ» 58 Β· π 370 Β· π¦ 5.2K Β· π 590 - 23% open Β· β±οΈ 12.12.2024):
```
git clone https://github.com/holoviz/datashader
```
- [PyPi](https://pypi.org/project/datashader) (π₯ 160K / month Β· π¦ 200 Β· β±οΈ 04.07.2024):
```
pip install datashader
```
- [Conda](https://anaconda.org/conda-forge/datashader) (π₯ 1.3M Β· β±οΈ 16.12.2024):
```
conda install -c conda-forge datashader
```
</details>
<details><summary><b><a href="https://github.com/vispy/vispy">VisPy</a></b> (π₯34 Β· β 3.3K) - High-performance interactive 2D/3D data visualization library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/vispy/vispy) (π¨βπ» 200 Β· π 620 Β· π¦ 1.8K Β· π 1.5K - 24% open Β· β±οΈ 09.11.2024):
```
git clone https://github.com/vispy/vispy
```
- [PyPi](https://pypi.org/project/vispy) (π₯ 710K / month Β· π¦ 170 Β· β±οΈ 17.06.2024):
```
pip install vispy
```
- [Conda](https://anaconda.org/conda-forge/vispy) (π₯ 660K Β· β±οΈ 04.09.2024):
```
conda install -c conda-forge vispy
```
- [npm](https://www.npmjs.com/package/vispy) (π₯ 15 / month Β· π¦ 3 Β· β±οΈ 15.03.2020):
```
npm install vispy
```
</details>
<details><summary><b><a href="https://github.com/amueller/word_cloud">wordcloud</a></b> (π₯33 Β· β 10K) - A little word cloud generator in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/amueller/word_cloud) (π¨βπ» 72 Β· π 2.3K Β· π¦ 21 Β· π 550 - 23% open Β· β±οΈ 10.11.2024):
```
git clone https://github.com/amueller/word_cloud
```
- [PyPi](https://pypi.org/project/wordcloud) (π₯ 1.9M / month Β· π¦ 550 Β· β±οΈ 10.11.2024):
```
pip install wordcloud
```
- [Conda](https://anaconda.org/conda-forge/wordcloud) (π₯ 580K Β· β±οΈ 02.12.2024):
```
conda install -c conda-forge wordcloud
```
</details>
<details><summary><b><a href="https://github.com/JetBrains/lets-plot">lets-plot</a></b> (π₯32 Β· β 1.6K) - Multiplatform plotting library based on the Grammar of Graphics. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/JetBrains/lets-plot) (π¨βπ» 21 Β· π 52 Β· π₯ 1.4K Β· π¦ 150 Β· π 650 - 24% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/JetBrains/lets-plot
```
- [PyPi](https://pypi.org/project/lets-plot) (π₯ 50K / month Β· π¦ 15 Β· β±οΈ 17.12.2024):
```
pip install lets-plot
```
</details>
<details><summary><b><a href="https://github.com/holoviz/hvplot">hvPlot</a></b> (π₯32 Β· β 1.2K) - A high-level plotting API for pandas, dask, xarray, and networkx built.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/holoviz/hvplot) (π¨βπ» 51 Β· π 110 Β· π¦ 6.3K Β· π 830 - 43% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/holoviz/hvplot
```
- [PyPi](https://pypi.org/project/hvplot) (π₯ 200K / month Β· π¦ 220 Β· β±οΈ 16.12.2024):
```
pip install hvplot
```
- [Conda](https://anaconda.org/conda-forge/hvplot) (π₯ 690K Β· β±οΈ 16.12.2024):
```
conda install -c conda-forge hvplot
```
</details>
<details><summary><b><a href="https://github.com/man-group/dtale">D-Tale</a></b> (π₯31 Β· β 4.8K) - Visualizer for pandas data structures. <code><a href="https://tldrlegal.com/search?q=LGPL-2.1">βοΈLGPL-2.1</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/man-group/dtale) (π¨βπ» 30 Β· π 410 Β· π¦ 1.3K Β· π 590 - 10% open Β· β±οΈ 13.12.2024):
```
git clone https://github.com/man-group/dtale
```
- [PyPi](https://pypi.org/project/dtale) (π₯ 90K / month Β· π¦ 48 Β· β±οΈ 13.12.2024):
```
pip install dtale
```
- [Conda](https://anaconda.org/conda-forge/dtale) (π₯ 360K Β· β±οΈ 13.12.2024):
```
conda install -c conda-forge dtale
```
</details>
<details><summary><b><a href="https://github.com/mpld3/mpld3">mpld3</a></b> (π₯31 Β· β 2.4K) - An interactive data visualization tool which brings matplotlib graphics to.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/mpld3/mpld3) (π¨βπ» 53 Β· π 360 Β· π¦ 6.8K Β· π 370 - 59% open Β· β±οΈ 30.10.2024):
```
git clone https://github.com/mpld3/mpld3
```
- [PyPi](https://pypi.org/project/mpld3) (π₯ 340K / month Β· π¦ 150 Β· β±οΈ 23.12.2023):
```
pip install mpld3
```
- [Conda](https://anaconda.org/conda-forge/mpld3) (π₯ 220K Β· β±οΈ 23.12.2023):
```
conda install -c conda-forge mpld3
```
- [npm](https://www.npmjs.com/package/mpld3) (π₯ 1.1K / month Β· π¦ 9 Β· β±οΈ 23.12.2023):
```
npm install mpld3
```
</details>
<details><summary><b><a href="https://github.com/bqplot/bqplot">bqplot</a></b> (π₯29 Β· β 3.6K) - Plotting library for IPython/Jupyter notebooks. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/bqplot/bqplot) (π¨βπ» 65 Β· π 460 Β· π¦ 59 Β· π 640 - 42% open Β· β±οΈ 22.10.2024):
```
git clone https://github.com/bqplot/bqplot
```
- [PyPi](https://pypi.org/project/bqplot) (π₯ 210K / month Β· π¦ 99 Β· β±οΈ 25.03.2024):
```
pip install bqplot
```
- [Conda](https://anaconda.org/conda-forge/bqplot) (π₯ 1.4M Β· β±οΈ 16.12.2024):
```
conda install -c conda-forge bqplot
```
- [npm](https://www.npmjs.com/package/bqplot) (π₯ 2.4K / month Β· π¦ 21 Β· β±οΈ 25.03.2024):
```
npm install bqplot
```
</details>
<details><summary><b><a href="https://github.com/spotify/chartify">Chartify</a></b> (π₯27 Β· β 3.5K) - Python library that makes it easy for data scientists to create.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/spotify/chartify) (π¨βπ» 27 Β· π 320 Β· π¦ 80 Β· π 83 - 61% open Β· β±οΈ 16.10.2024):
```
git clone https://github.com/spotify/chartify
```
- [PyPi](https://pypi.org/project/chartify) (π₯ 2.3K / month Β· π¦ 9 Β· β±οΈ 16.10.2024):
```
pip install chartify
```
- [Conda](https://anaconda.org/conda-forge/chartify) (π₯ 34K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge chartify
```
</details>
<details><summary><b><a href="https://github.com/pavlin-policar/openTSNE">openTSNE</a></b> (π₯27 Β· β 1.5K) - Extensible, parallel implementations of t-SNE. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/pavlin-policar/openTSNE) (π¨βπ» 13 Β· π 160 Β· π¦ 940 Β· π 140 - 6% open Β· β±οΈ 24.10.2024):
```
git clone https://github.com/pavlin-policar/openTSNE
```
- [PyPi](https://pypi.org/project/opentsne) (π₯ 46K / month Β· π¦ 47 Β· β±οΈ 13.08.2024):
```
pip install opentsne
```
- [Conda](https://anaconda.org/conda-forge/opentsne) (π₯ 350K Β· β±οΈ 16.11.2024):
```
conda install -c conda-forge opentsne
```
</details>
<details><summary><b><a href="https://github.com/ContextLab/hypertools">HyperTools</a></b> (π₯26 Β· β 1.8K Β· π€) - A Python toolbox for gaining geometric insights into high-.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/ContextLab/hypertools) (π¨βπ» 22 Β· π 160 Β· π₯ 57 Β· π¦ 490 Β· π 200 - 34% open Β· β±οΈ 19.03.2024):
```
git clone https://github.com/ContextLab/hypertools
```
- [PyPi](https://pypi.org/project/hypertools) (π₯ 1.3K / month Β· π¦ 2 Β· β±οΈ 12.02.2022):
```
pip install hypertools
```
</details>
<details><summary><b><a href="https://github.com/predict-idlab/plotly-resampler">Plotly-Resampler</a></b> (π₯26 Β· β 1.1K) - Visualize large time series data with plotly.py. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/predict-idlab/plotly-resampler) (π¨βπ» 14 Β· π 69 Β· π¦ 1.6K Β· π 170 - 32% open Β· β±οΈ 15.12.2024):
```
git clone https://github.com/predict-idlab/plotly-resampler
```
- [PyPi](https://pypi.org/project/plotly-resampler) (π₯ 480K / month Β· π¦ 24 Β· β±οΈ 27.03.2024):
```
pip install plotly-resampler
```
- [Conda](https://anaconda.org/conda-forge/plotly-resampler) (π₯ 81K Β· β±οΈ 05.12.2024):
```
conda install -c conda-forge plotly-resampler
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/data-validation">data-validation</a></b> (π₯26 Β· β 760) - Library for exploring and validating machine learning.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/data-validation) (π¨βπ» 27 Β· π 170 Β· π₯ 920 Β· π 180 - 21% open Β· β±οΈ 20.11.2024):
```
git clone https://github.com/tensorflow/data-validation
```
- [PyPi](https://pypi.org/project/tensorflow-data-validation) (π₯ 150K / month Β· π¦ 31 Β· β±οΈ 15.10.2024):
```
pip install tensorflow-data-validation
```
</details>
<details><summary><b><a href="https://github.com/AutoViML/AutoViz">AutoViz</a></b> (π₯25 Β· β 1.8K) - Automatically Visualize any dataset, any size with a single line of.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/AutoViML/AutoViz) (π¨βπ» 17 Β· π 200 Β· π¦ 790 Β· π 95 - 4% open Β· β±οΈ 10.06.2024):
```
git clone https://github.com/AutoViML/AutoViz
```
- [PyPi](https://pypi.org/project/autoviz) (π₯ 20K / month Β· π¦ 11 Β· β±οΈ 10.06.2024):
```
pip install autoviz
```
- [Conda](https://anaconda.org/conda-forge/autoviz) (π₯ 71K Β· β±οΈ 26.04.2024):
```
conda install -c conda-forge autoviz
```
</details>
<details><summary><b><a href="https://github.com/marcharper/python-ternary">python-ternary</a></b> (π₯24 Β· β 740) - Ternary plotting library for python with matplotlib. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/marcharper/python-ternary) (π¨βπ» 28 Β· π 160 Β· π₯ 35 Β· π¦ 200 Β· π 140 - 24% open Β· β±οΈ 12.06.2024):
```
git clone https://github.com/marcharper/python-ternary
```
- [PyPi](https://pypi.org/project/python-ternary) (π₯ 18K / month Β· π¦ 32 Β· β±οΈ 17.02.2021):
```
pip install python-ternary
```
- [Conda](https://anaconda.org/conda-forge/python-ternary) (π₯ 94K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge python-ternary
```
</details>
<details><summary><b><a href="https://github.com/vega/ipyvega">vega</a></b> (π₯24 Β· β 380) - IPython/Jupyter notebook module for Vega and Vega-Lite. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/vega/ipyvega) (π¨βπ» 15 Β· π 65 Β· π¦ 4 Β· π 110 - 14% open Β· β±οΈ 01.12.2024):
```
git clone https://github.com/vega/ipyvega
```
- [PyPi](https://pypi.org/project/vega) (π₯ 10K / month Β· π¦ 17 Β· β±οΈ 25.09.2024):
```
pip install vega
```
- [Conda](https://anaconda.org/conda-forge/vega) (π₯ 680K Β· β±οΈ 25.09.2024):
```
conda install -c conda-forge vega
```
</details>
<details><summary><b><a href="https://github.com/DmitryUlyanov/Multicore-TSNE">Multicore-TSNE</a></b> (π₯23 Β· β 1.9K Β· π€) - Parallel t-SNE implementation with Python and Torch.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/DmitryUlyanov/Multicore-TSNE) (π¨βπ» 18 Β· π 230 Β· π¦ 480 Β· π 69 - 65% open Β· β±οΈ 06.02.2024):
```
git clone https://github.com/DmitryUlyanov/Multicore-TSNE
```
- [PyPi](https://pypi.org/project/MulticoreTSNE) (π₯ 1.5K / month Β· π¦ 22 Β· β±οΈ 09.01.2019):
```
pip install MulticoreTSNE
```
- [Conda](https://anaconda.org/conda-forge/multicore-tsne) (π₯ 57K Β· β±οΈ 11.10.2023):
```
conda install -c conda-forge multicore-tsne
```
</details>
<details><summary><b><a href="https://github.com/vega/vegafusion">vegafusion</a></b> (π₯23 Β· β 340) - Serverside scaling for Vega and Altair visualizations. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/vega/vegafusion) (π¨βπ» 5 Β· π 18 Β· π₯ 9K Β· π 140 - 36% open Β· β±οΈ 25.11.2024):
```
git clone https://github.com/vegafusion/vegafusion
```
- [PyPi](https://pypi.org/project/vegafusion-jupyter) (π₯ 2.2K / month Β· π¦ 2 Β· β±οΈ 09.05.2024):
```
pip install vegafusion-jupyter
```
- [Conda](https://anaconda.org/conda-forge/vegafusion-python-embed) (π₯ 290K Β· β±οΈ 31.10.2024):
```
conda install -c conda-forge vegafusion-python-embed
```
- [npm](https://www.npmjs.com/package/vegafusion-jupyter) (π₯ 180 / month Β· π¦ 3 Β· β±οΈ 09.05.2024):
```
npm install vegafusion-jupyter
```
</details>
<details><summary><b><a href="https://github.com/beringresearch/ivis">ivis</a></b> (π₯22 Β· β 330) - Dimensionality reduction in very large datasets using Siamese.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/beringresearch/ivis) (π¨βπ» 10 Β· π 43 Β· π¦ 36 Β· π 60 - 5% open Β· β±οΈ 29.09.2024):
```
git clone https://github.com/beringresearch/ivis
```
- [PyPi](https://pypi.org/project/ivis) (π₯ 1.3K / month Β· π¦ 2 Β· β±οΈ 13.06.2024):
```
pip install ivis
```
</details>
<details><summary><b><a href="https://github.com/gyli/PyWaffle">PyWaffle</a></b> (π₯21 Β· β 590) - Make Waffle Charts in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/gyli/PyWaffle) (π¨βπ» 6 Β· π 110 Β· π¦ 440 Β· π 22 - 27% open Β· β±οΈ 16.06.2024):
```
git clone https://github.com/gyli/PyWaffle
```
- [PyPi](https://pypi.org/project/pywaffle) (π₯ 9.9K / month Β· π¦ 6 Β· β±οΈ 16.06.2024):
```
pip install pywaffle
```
- [Conda](https://anaconda.org/conda-forge/pywaffle) (π₯ 14K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge pywaffle
```
</details>
<details><summary><b><a href="https://github.com/t-makaro/animatplot">animatplot</a></b> (π₯19 Β· β 410) - A python package for animating plots build on matplotlib. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/t-makaro/animatplot) (π¨βπ» 6 Β· π 38 Β· π¦ 62 Β· π 37 - 45% open Β· β±οΈ 29.08.2024):
```
git clone https://github.com/t-makaro/animatplot
```
- [PyPi](https://pypi.org/project/animatplot) (π₯ 600 / month Β· π¦ 4 Β· β±οΈ 29.08.2024):
```
pip install animatplot
```
- [Conda](https://anaconda.org/conda-forge/animatplot) (π₯ 15K Β· β±οΈ 01.09.2024):
```
conda install -c conda-forge animatplot
```
</details>
<details><summary>Show 17 hidden projects...</summary>
- <b><a href="https://github.com/ResidentMario/missingno">missingno</a></b> (π₯29 Β· β 4K Β· π) - Missing data visualization module for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/santosjorge/cufflinks">Cufflinks</a></b> (π₯28 Β· β 3K Β· π) - Productivity Tools for Plotly + Pandas. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/jupyter-widgets/pythreejs">pythreejs</a></b> (π₯28 Β· β 960 Β· π) - A Jupyter - Three.js bridge. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/PAIR-code/facets">Facets Overview</a></b> (π₯27 Β· β 7.4K Β· π) - Visualizations for machine learning datasets. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/fbdesignpro/sweetviz">Sweetviz</a></b> (π₯26 Β· β 3K Β· π) - Visualize and compare datasets, target values and associations, with.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/tpvasconcelos/ridgeplot">ridgeplot</a></b> (π₯25 Β· β 190) - Beautiful ridgeline plots in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/facebookresearch/hiplot">HiPlot</a></b> (π₯24 Β· β 2.8K Β· π) - HiPlot makes understanding high dimensional data easy. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/adamerose/PandasGUI">PandasGUI</a></b> (π₯23 Β· β 3.2K Β· π€) - A GUI for Pandas DataFrames. <code><a href="https://tldrlegal.com/search?q=MIT-0">βοΈMIT-0</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/PatrikHlobil/Pandas-Bokeh">Pandas-Bokeh</a></b> (π₯23 Β· β 880 Β· π) - Bokeh Plotting Backend for Pandas and GeoPandas. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/nicolaskruchten/jupyter_pivottablejs">pivottablejs</a></b> (π₯22 Β· β 690 Β· π) - Dragndrop Pivot Tables and Charts for Jupyter/IPython.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/leotac/joypy">joypy</a></b> (π₯21 Β· β 560 Β· π) - Joyplots in Python with matplotlib & pandas. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/SauceCat/PDPbox">PDPbox</a></b> (π₯20 Β· β 850 Β· π) - python partial dependence plot toolbox. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/ing-bank/popmon">Popmon</a></b> (π₯18 Β· β 500 Β· π) - Monitor the stability of a Pandas or Spark dataframe. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/altair-viz/pdvega">pdvega</a></b> (π₯16 Β· β 340 Β· π) - Interactive plotting for Pandas using Vega-Lite. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/data-describe/data-describe">data-describe</a></b> (π₯15 Β· β 300 Β· π) - datadescribe: Pythonic EDA Accelerator for Data Science. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/Zsailer/nx_altair">nx-altair</a></b> (π₯15 Β· β 220 Β· π) - Draw interactive NetworkX graphs with Altair. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/biovault/nptsne">nptsne</a></b> (π₯13 Β· β 32 Β· π) - nptsne is a numpy compatible python binary package that offers a.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
</details>
<br>
## Text Data & NLP
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for processing, cleaning, manipulating, and analyzing text data as well as libraries for NLP tasks such as language detection, fuzzy matching, classification, seq2seq learning, conversational AI, keyword extraction, and translation._
<details><summary><b><a href="https://github.com/huggingface/transformers">transformers</a></b> (π₯52 Β· β 140K) - Transformers: State-of-the-art Machine Learning for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/huggingface/transformers) (π¨βπ» 3K Β· π 27K Β· π¦ 260K Β· π 17K - 8% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/huggingface/transformers
```
- [PyPi](https://pypi.org/project/transformers) (π₯ 49M / month Β· π¦ 7.1K Β· β±οΈ 17.12.2024):
```
pip install transformers
```
- [Conda](https://anaconda.org/conda-forge/transformers) (π₯ 2.3M Β· β±οΈ 18.12.2024):
```
conda install -c conda-forge transformers
```
</details>
<details><summary><b><a href="https://github.com/explosion/spaCy">spaCy</a></b> (π₯45 Β· β 30K) - Industrial-strength Natural Language Processing (NLP) in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/explosion/spaCy) (π¨βπ» 760 Β· π 4.4K Β· π₯ 990 Β· π¦ 110K Β· π 5.7K - 2% open Β· β±οΈ 11.12.2024):
```
git clone https://github.com/explosion/spaCy
```
- [PyPi](https://pypi.org/project/spacy) (π₯ 15M / month Β· π¦ 2.8K Β· β±οΈ 11.12.2024):
```
pip install spacy
```
- [Conda](https://anaconda.org/conda-forge/spacy) (π₯ 4.8M Β· β±οΈ 24.11.2024):
```
conda install -c conda-forge spacy
```
</details>
<details><summary><b><a href="https://github.com/BerriAI/litellm">litellm</a></b> (π₯44 Β· β 15K) - Python SDK, Proxy Server (LLM Gateway) to call 100+.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code>o</code> <code>t</code> <code>h</code> <code>e</code> <code>r</code> <code>s</code></summary>
- [GitHub](https://github.com/BerriAI/litellm) (π¨βπ» 370 Β· π 1.8K Β· π₯ 470 Β· π¦ 5.3K Β· π 4K - 23% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/BerriAI/litellm
```
- [PyPi](https://pypi.org/project/litellm) (π₯ 3.4M / month Β· π¦ 630 Β· β±οΈ 19.12.2024):
```
pip install litellm
```
</details>
<details><summary><b><a href="https://github.com/nltk/nltk">nltk</a></b> (π₯44 Β· β 14K) - Suite of libraries and programs for symbolic and statistical natural.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/nltk/nltk) (π¨βπ» 460 Β· π 2.9K Β· π¦ 330K Β· π 1.8K - 14% open Β· β±οΈ 11.11.2024):
```
git clone https://github.com/nltk/nltk
```
- [PyPi](https://pypi.org/project/nltk) (π₯ 25M / month Β· π¦ 4.7K Β· β±οΈ 18.08.2024):
```
pip install nltk
```
- [Conda](https://anaconda.org/conda-forge/nltk) (π₯ 2.9M Β· β±οΈ 16.12.2024):
```
conda install -c conda-forge nltk
```
</details>
<details><summary><b><a href="https://github.com/UKPLab/sentence-transformers">sentence-transformers</a></b> (π₯41 Β· β 16K) - State-of-the-Art Text Embeddings. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/UKPLab/sentence-transformers) (π¨βπ» 200 Β· π 2.5K Β· π¦ 61K Β· π 2.3K - 52% open Β· β±οΈ 12.12.2024):
```
git clone https://github.com/UKPLab/sentence-transformers
```
- [PyPi](https://pypi.org/project/sentence-transformers) (π₯ 8.1M / month Β· π¦ 1.8K Β· β±οΈ 18.11.2024):
```
pip install sentence-transformers
```
- [Conda](https://anaconda.org/conda-forge/sentence-transformers) (π₯ 500K Β· β±οΈ 18.11.2024):
```
conda install -c conda-forge sentence-transformers
```
</details>
<details><summary><b><a href="https://github.com/flairNLP/flair">flair</a></b> (π₯41 Β· β 14K Β· π) - A very simple framework for state-of-the-art Natural Language.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/flairNLP/flair) (π¨βπ» 270 Β· π 2.1K Β· π¦ 3.7K Β· π 2.4K - 5% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/flairNLP/flair
```
- [PyPi](https://pypi.org/project/flair) (π₯ 100K / month Β· π¦ 140 Β· β±οΈ 25.07.2024):
```
pip install flair
```
- [Conda](https://anaconda.org/conda-forge/python-flair) (π₯ 35K Β· β±οΈ 05.01.2024):
```
conda install -c conda-forge python-flair
```
</details>
<details><summary><b><a href="https://github.com/huggingface/tokenizers">Tokenizers</a></b> (π₯40 Β· β 9.2K) - Fast State-of-the-Art Tokenizers optimized for Research and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/huggingface/tokenizers) (π¨βπ» 100 Β· π 810 Β· π₯ 69 Β· π¦ 120K Β· π 1K - 5% open Β· β±οΈ 27.11.2024):
```
git clone https://github.com/huggingface/tokenizers
```
- [PyPi](https://pypi.org/project/tokenizers) (π₯ 36M / month Β· π¦ 1.1K Β· β±οΈ 27.11.2024):
```
pip install tokenizers
```
- [Conda](https://anaconda.org/conda-forge/tokenizers) (π₯ 2.4M Β· β±οΈ 27.11.2024):
```
conda install -c conda-forge tokenizers
```
</details>
<details><summary><b><a href="https://github.com/piskvorky/gensim">gensim</a></b> (π₯39 Β· β 16K) - Topic Modelling for Humans. <code><a href="https://tldrlegal.com/search?q=LGPL-2.1">βοΈLGPL-2.1</a></code></summary>
- [GitHub](https://github.com/piskvorky/gensim) (π¨βπ» 460 Β· π 4.4K Β· π₯ 5.2K Β· π¦ 68K Β· π 1.8K - 20% open Β· β±οΈ 05.12.2024):
```
git clone https://github.com/RaRe-Technologies/gensim
```
- [PyPi](https://pypi.org/project/gensim) (π₯ 4.8M / month Β· π¦ 1.4K Β· β±οΈ 19.07.2024):
```
pip install gensim
```
- [Conda](https://anaconda.org/conda-forge/gensim) (π₯ 1.5M Β· β±οΈ 03.09.2024):
```
conda install -c conda-forge gensim
```
</details>
<details><summary><b><a href="https://github.com/google/sentencepiece">sentencepiece</a></b> (π₯38 Β· β 10K) - Unsupervised text tokenizer for Neural Network-based text.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/google/sentencepiece) (π¨βπ» 89 Β· π 1.2K Β· π₯ 47K Β· π¦ 88K Β· π 760 - 5% open Β· β±οΈ 18.08.2024):
```
git clone https://github.com/google/sentencepiece
```
- [PyPi](https://pypi.org/project/sentencepiece) (π₯ 26M / month Β· π¦ 1.7K Β· β±οΈ 19.02.2024):
```
pip install sentencepiece
```
- [Conda](https://anaconda.org/conda-forge/sentencepiece) (π₯ 1.2M Β· β±οΈ 25.11.2024):
```
conda install -c conda-forge sentencepiece
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/fairseq">fairseq</a></b> (π₯37 Β· β 31K) - Facebook AI Research Sequence-to-Sequence Toolkit written in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/facebookresearch/fairseq) (π¨βπ» 430 Β· π 6.4K Β· π₯ 370 Β· π¦ 3.8K Β· π 4.3K - 29% open Β· β±οΈ 18.10.2024):
```
git clone https://github.com/facebookresearch/fairseq
```
- [PyPi](https://pypi.org/project/fairseq) (π₯ 130K / month Β· π¦ 120 Β· β±οΈ 27.06.2022):
```
pip install fairseq
```
- [Conda](https://anaconda.org/conda-forge/fairseq) (π₯ 110K Β· β±οΈ 24.11.2024):
```
conda install -c conda-forge fairseq
```
</details>
<details><summary><b><a href="https://github.com/RasaHQ/rasa">Rasa</a></b> (π₯37 Β· β 19K) - Open source machine learning framework to automate text- and voice-.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/RasaHQ/rasa) (π¨βπ» 600 Β· π 4.7K Β· π¦ 4.7K Β· π 6.8K - 1% open Β· β±οΈ 25.11.2024):
```
git clone https://github.com/RasaHQ/rasa
```
- [PyPi](https://pypi.org/project/rasa) (π₯ 200K / month Β· π¦ 60 Β· β±οΈ 18.04.2024):
```
pip install rasa
```
</details>
<details><summary><b><a href="https://github.com/NVIDIA/NeMo">NeMo</a></b> (π₯37 Β· β 12K) - A scalable generative AI framework built for researchers and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/NVIDIA/NeMo) (π¨βπ» 370 Β· π 2.6K Β· π₯ 280K Β· π¦ 21 Β· π 2.4K - 5% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/NVIDIA/NeMo
```
- [PyPi](https://pypi.org/project/nemo-toolkit) (π₯ 130K / month Β· π¦ 13 Β· β±οΈ 11.12.2024):
```
pip install nemo-toolkit
```
</details>
<details><summary><b><a href="https://github.com/sloria/TextBlob">TextBlob</a></b> (π₯36 Β· β 9.2K) - Simple, Pythonic, text processing--Sentiment analysis, part-of-speech.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/sloria/TextBlob) (π¨βπ» 37 Β· π 1.2K Β· π₯ 120 Β· π¦ 47K Β· π 280 - 39% open Β· β±οΈ 07.08.2024):
```
git clone https://github.com/sloria/TextBlob
```
- [PyPi](https://pypi.org/project/textblob) (π₯ 1.3M / month Β· π¦ 390 Β· β±οΈ 15.02.2024):
```
pip install textblob
```
- [Conda](https://anaconda.org/conda-forge/textblob) (π₯ 270K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge textblob
```
</details>
<details><summary><b><a href="https://github.com/JohnSnowLabs/spark-nlp">spark-nlp</a></b> (π₯36 Β· β 3.9K) - State of the Art Natural Language Processing. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/JohnSnowLabs/spark-nlp) (π¨βπ» 110 Β· π 720 Β· π¦ 530 Β· π 900 - 3% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/JohnSnowLabs/spark-nlp
```
- [PyPi](https://pypi.org/project/spark-nlp) (π₯ 4.1M / month Β· π¦ 37 Β· β±οΈ 18.12.2024):
```
pip install spark-nlp
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/text">TensorFlow Text</a></b> (π₯36 Β· β 1.2K) - Making text a first-class citizen in TensorFlow. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/text) (π¨βπ» 160 Β· π 350 Β· π¦ 7.7K Β· π 360 - 52% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/tensorflow/text
```
- [PyPi](https://pypi.org/project/tensorflow-text) (π₯ 9.3M / month Β· π¦ 220 Β· β±οΈ 16.12.2024):
```
pip install tensorflow-text
```
</details>
<details><summary><b><a href="https://github.com/deepset-ai/haystack">haystack</a></b> (π₯35 Β· β 18K) - AI orchestration framework to build customizable, production-ready.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/deepset-ai/haystack) (π¨βπ» 270 Β· π 1.9K Β· π¦ 700 Β· π 3.6K - 3% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/deepset-ai/haystack
```
- [PyPi](https://pypi.org/project/haystack) (π₯ 6.3K / month Β· π¦ 5 Β· β±οΈ 15.12.2021):
```
pip install haystack
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/fastText">fastText</a></b> (π₯34 Β· β 26K Β· π€) - Library for fast text representation and classification. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/facebookresearch/fastText) (π¨βπ» 68 Β· π 4.7K Β· π¦ 7K Β· π 1.2K - 47% open Β· β±οΈ 13.03.2024):
```
git clone https://github.com/facebookresearch/fastText
```
- [PyPi](https://pypi.org/project/fasttext) (π₯ 1.6M / month Β· π¦ 250 Β· β±οΈ 12.06.2024):
```
pip install fasttext
```
- [Conda](https://anaconda.org/conda-forge/fasttext) (π₯ 110K Β· β±οΈ 19.05.2024):
```
conda install -c conda-forge fasttext
```
</details>
<details><summary><b><a href="https://github.com/argilla-io/argilla">rubrix</a></b> (π₯34 Β· β 4.1K) - Argilla is a collaboration tool for AI engineers and domain experts.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/argilla-io/argilla) (π¨βπ» 100 Β· π 380 Β· π¦ 2.8K Β· π 2.2K - 4% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/recognai/rubrix
```
- [PyPi](https://pypi.org/project/rubrix) (π₯ 2K / month Β· β±οΈ 24.10.2022):
```
pip install rubrix
```
- [Conda](https://anaconda.org/conda-forge/rubrix) (π₯ 40K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge rubrix
```
</details>
<details><summary><b><a href="https://github.com/qdrant/qdrant">qdrant</a></b> (π₯33 Β· β 21K) - Qdrant - High-performance, massive-scale Vector Database and Vector.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/qdrant/qdrant) (π¨βπ» 130 Β· π 1.4K Β· π₯ 270K Β· π¦ 120 Β· π 1.4K - 25% open Β· β±οΈ 09.12.2024):
```
git clone https://github.com/qdrant/qdrant
```
</details>
<details><summary><b><a href="https://github.com/rspeer/python-ftfy">ftfy</a></b> (π₯33 Β· β 3.8K) - Fixes mojibake and other glitches in Unicode text, after the fact. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/rspeer/python-ftfy) (π¨βπ» 20 Β· π 120 Β· π₯ 26 Β· π¦ 25K Β· π 140 - 5% open Β· β±οΈ 30.10.2024):
```
git clone https://github.com/rspeer/python-ftfy
```
- [PyPi](https://pypi.org/project/ftfy) (π₯ 4.6M / month Β· π¦ 570 Β· β±οΈ 26.10.2024):
```
pip install ftfy
```
- [Conda](https://anaconda.org/conda-forge/ftfy) (π₯ 310K Β· β±οΈ 26.10.2024):
```
conda install -c conda-forge ftfy
```
</details>
<details><summary><b><a href="https://github.com/pytorch/text">torchtext</a></b> (π₯33 Β· β 3.5K) - Models, data loaders and abstractions for language processing,.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pytorch/text) (π¨βπ» 160 Β· π 810 Β· π 850 - 39% open Β· β±οΈ 14.08.2024):
```
git clone https://github.com/pytorch/text
```
- [PyPi](https://pypi.org/project/torchtext) (π₯ 1M / month Β· π¦ 280 Β· β±οΈ 24.04.2024):
```
pip install torchtext
```
</details>
<details><summary><b><a href="https://github.com/jamesturk/jellyfish">jellyfish</a></b> (π₯33 Β· β 2.1K) - a python library for doing approximate and phonetic matching of strings. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/jamesturk/jellyfish) (π¨βπ» 34 Β· π 160 Β· π¦ 12K Β· π 140 - 4% open Β· β±οΈ 14.12.2024):
```
git clone https://github.com/jamesturk/jellyfish
```
- [PyPi](https://pypi.org/project/jellyfish) (π₯ 6.8M / month Β· π¦ 280 Β· β±οΈ 14.12.2024):
```
pip install jellyfish
```
- [Conda](https://anaconda.org/conda-forge/jellyfish) (π₯ 1.1M Β· β±οΈ 17.12.2024):
```
conda install -c conda-forge jellyfish
```
</details>
<details><summary><b><a href="https://github.com/stanfordnlp/stanza">stanza</a></b> (π₯32 Β· β 7.3K) - Stanford NLP Python library for tokenization, sentence segmentation,.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/stanfordnlp/stanza) (π¨βπ» 68 Β· π 900 Β· π¦ 3.3K Β· π 910 - 11% open Β· β±οΈ 12.09.2024):
```
git clone https://github.com/stanfordnlp/stanza
```
- [PyPi](https://pypi.org/project/stanza) (π₯ 270K / month Β· π¦ 180 Β· β±οΈ 12.09.2024):
```
pip install stanza
```
- [Conda](https://anaconda.org/stanfordnlp/stanza) (π₯ 8.3K Β· β±οΈ 16.06.2023):
```
conda install -c stanfordnlp stanza
```
</details>
<details><summary><b><a href="https://github.com/OpenNMT/OpenNMT-py">OpenNMT</a></b> (π₯32 Β· β 6.8K) - Open Source Neural Machine Translation and (Large) Language Models.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/OpenNMT/OpenNMT-py) (π¨βπ» 190 Β· π 2.2K Β· π¦ 300 Β· π 1.5K - 1% open Β· β±οΈ 27.06.2024):
```
git clone https://github.com/OpenNMT/OpenNMT-py
```
- [PyPi](https://pypi.org/project/OpenNMT-py) (π₯ 16K / month Β· π¦ 23 Β· β±οΈ 18.03.2024):
```
pip install OpenNMT-py
```
</details>
<details><summary><b><a href="https://github.com/deeppavlov/DeepPavlov">DeepPavlov</a></b> (π₯31 Β· β 6.8K) - An open source library for deep learning end-to-end dialog.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/deeppavlov/DeepPavlov) (π¨βπ» 77 Β· π 1.2K Β· π¦ 420 Β· π 640 - 4% open Β· β±οΈ 26.11.2024):
```
git clone https://github.com/deepmipt/DeepPavlov
```
- [PyPi](https://pypi.org/project/deeppavlov) (π₯ 12K / month Β· π¦ 4 Β· β±οΈ 12.08.2024):
```
pip install deeppavlov
```
</details>
<details><summary><b><a href="https://github.com/snowballstem/snowball">snowballstemmer</a></b> (π₯31 Β· β 760) - Snowball compiler and stemming algorithms. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/snowballstem/snowball) (π¨βπ» 35 Β· π 170 Β· π¦ 10 Β· π 90 - 27% open Β· β±οΈ 20.11.2024):
```
git clone https://github.com/snowballstem/snowball
```
- [PyPi](https://pypi.org/project/snowballstemmer) (π₯ 26M / month Β· π¦ 450 Β· β±οΈ 16.11.2021):
```
pip install snowballstemmer
```
- [Conda](https://anaconda.org/conda-forge/snowballstemmer) (π₯ 9M Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge snowballstemmer
```
</details>
<details><summary><b><a href="https://github.com/dedupeio/dedupe">Dedupe</a></b> (π₯30 Β· β 4.2K) - A python library for accurate and scalable fuzzy matching, record.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/dedupeio/dedupe) (π¨βπ» 72 Β· π 550 Β· π¦ 350 Β· π 820 - 9% open Β· β±οΈ 01.11.2024):
```
git clone https://github.com/dedupeio/dedupe
```
- [PyPi](https://pypi.org/project/dedupe) (π₯ 93K / month Β· π¦ 19 Β· β±οΈ 15.08.2024):
```
pip install dedupe
```
- [Conda](https://anaconda.org/conda-forge/dedupe) (π₯ 87K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge dedupe
```
</details>
<details><summary><b><a href="https://github.com/allenai/scispacy">SciSpacy</a></b> (π₯30 Β· β 1.7K) - A full spaCy pipeline and models for scientific/biomedical documents. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/allenai/scispacy) (π¨βπ» 37 Β· π 230 Β· π¦ 1K Β· π 320 - 9% open Β· β±οΈ 23.11.2024):
```
git clone https://github.com/allenai/scispacy
```
- [PyPi](https://pypi.org/project/scispacy) (π₯ 21K / month Β· π¦ 34 Β· β±οΈ 27.10.2024):
```
pip install scispacy
```
</details>
<details><summary><b><a href="https://github.com/life4/textdistance">TextDistance</a></b> (π₯29 Β· β 3.4K) - Compute distance between sequences. 30+ algorithms, pure python.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/life4/textdistance) (π¨βπ» 17 Β· π 250 Β· π₯ 1K Β· π¦ 7.6K Β· β±οΈ 09.09.2024):
```
git clone https://github.com/life4/textdistance
```
- [PyPi](https://pypi.org/project/textdistance) (π₯ 730K / month Β· π¦ 99 Β· β±οΈ 16.07.2024):
```
pip install textdistance
```
- [Conda](https://anaconda.org/conda-forge/textdistance) (π₯ 690K Β· β±οΈ 17.07.2024):
```
conda install -c conda-forge textdistance
```
</details>
<details><summary><b><a href="https://github.com/explosion/spacy-transformers">spacy-transformers</a></b> (π₯29 Β· β 1.4K) - Use pretrained transformers like BERT, XLNet and GPT-2.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code>spacy</code></summary>
- [GitHub](https://github.com/explosion/spacy-transformers) (π¨βπ» 22 Β· π 170 Β· π¦ 2K Β· β±οΈ 05.06.2024):
```
git clone https://github.com/explosion/spacy-transformers
```
- [PyPi](https://pypi.org/project/spacy-transformers) (π₯ 270K / month Β· π¦ 87 Β· β±οΈ 25.04.2024):
```
pip install spacy-transformers
```
- [Conda](https://anaconda.org/conda-forge/spacy-transformers) (π₯ 78K Β· β±οΈ 11.12.2024):
```
conda install -c conda-forge spacy-transformers
```
</details>
<details><summary><b><a href="https://github.com/miso-belica/sumy">Sumy</a></b> (π₯28 Β· β 3.5K Β· π€) - Module for automatic summarization of text documents and HTML pages. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/miso-belica/sumy) (π¨βπ» 32 Β· π 530 Β· π¦ 3.3K Β· π 120 - 18% open Β· β±οΈ 16.05.2024):
```
git clone https://github.com/miso-belica/sumy
```
- [PyPi](https://pypi.org/project/sumy) (π₯ 170K / month Β· π¦ 31 Β· β±οΈ 23.10.2022):
```
pip install sumy
```
- [Conda](https://anaconda.org/conda-forge/sumy) (π₯ 10K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge sumy
```
</details>
<details><summary><b><a href="https://github.com/cltk/cltk">CLTK</a></b> (π₯28 Β· β 840) - The Classical Language Toolkit. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/cltk/cltk) (π¨βπ» 120 Β· π 330 Β· π₯ 110 Β· π¦ 280 Β· π 580 - 6% open Β· β±οΈ 01.12.2024):
```
git clone https://github.com/cltk/cltk
```
- [PyPi](https://pypi.org/project/cltk) (π₯ 5.4K / month Β· π¦ 17 Β· β±οΈ 01.12.2024):
```
pip install cltk
```
</details>
<details><summary><b><a href="https://github.com/zjunlp/DeepKE">DeepKE</a></b> (π₯27 Β· β 3.6K) - [EMNLP 2022] An Open Toolkit for Knowledge Graph Extraction and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/zjunlp/DeepKE) (π¨βπ» 32 Β· π 690 Β· π¦ 24 Β· π 580 - 1% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/zjunlp/deepke
```
- [PyPi](https://pypi.org/project/deepke) (π₯ 2K / month Β· β±οΈ 21.09.2023):
```
pip install deepke
```
</details>
<details><summary><b><a href="https://github.com/comet-ml/opik">Opik</a></b> (π₯27 Β· β 2.7K) - Open-source end-to-end LLM Development Platform. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/comet-ml/opik) (π¨βπ» 28 Β· π 170 Β· π 110 - 23% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/comet-ml/opik
```
- [PyPi](https://pypi.org/project/opik) (π₯ 11K / month Β· π¦ 1 Β· β±οΈ 18.12.2024):
```
pip install opik
```
</details>
<details><summary><b><a href="https://github.com/dwyl/english-words">english-words</a></b> (π₯26 Β· β 11K) - A text file containing 479k English words for all your.. <code><a href="http://bit.ly/3rvuUlR">Unlicense</a></code></summary>
- [GitHub](https://github.com/dwyl/english-words) (π¨βπ» 33 Β· π 1.8K Β· π¦ 2 Β· π 150 - 73% open Β· β±οΈ 11.12.2024):
```
git clone https://github.com/dwyl/english-words
```
- [PyPi](https://pypi.org/project/english-words) (π₯ 44K / month Β· π¦ 14 Β· β±οΈ 24.05.2023):
```
pip install english-words
```
</details>
<details><summary><b><a href="https://github.com/DerwenAI/pytextrank">PyTextRank</a></b> (π₯26 Β· β 2.2K Β· π€) - Python implementation of TextRank algorithms (textgraphs) for.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/DerwenAI/pytextrank) (π¨βπ» 19 Β· π 340 Β· π¦ 770 Β· π 100 - 12% open Β· β±οΈ 21.05.2024):
```
git clone https://github.com/DerwenAI/pytextrank
```
- [PyPi](https://pypi.org/project/pytextrank) (π₯ 81K / month Β· π¦ 19 Β· β±οΈ 21.02.2024):
```
pip install pytextrank
```
</details>
<details><summary><b><a href="https://github.com/JasonKessler/scattertext">scattertext</a></b> (π₯25 Β· β 2.3K) - Beautiful visualizations of how language differs among document.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/JasonKessler/scattertext) (π¨βπ» 14 Β· π 290 Β· π¦ 640 Β· π 100 - 21% open Β· β±οΈ 23.09.2024):
```
git clone https://github.com/JasonKessler/scattertext
```
- [PyPi](https://pypi.org/project/scattertext) (π₯ 12K / month Β· π¦ 5 Β· β±οΈ 23.09.2024):
```
pip install scattertext
```
- [Conda](https://anaconda.org/conda-forge/scattertext) (π₯ 100K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge scattertext
```
</details>
<details><summary><b><a href="https://github.com/google-research/text-to-text-transfer-transformer">T5</a></b> (π₯23 Β· β 6.2K) - Code for the paper Exploring the Limits of Transfer Learning with a.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/google-research/text-to-text-transfer-transformer) (π¨βπ» 59 Β· π 750 Β· π 450 - 23% open Β· β±οΈ 28.06.2024):
```
git clone https://github.com/google-research/text-to-text-transfer-transformer
```
- [PyPi](https://pypi.org/project/t5) (π₯ 31K / month Β· π¦ 2 Β· β±οΈ 18.10.2021):
```
pip install t5
```
</details>
<details><summary><b><a href="https://github.com/utterworks/fast-bert">fast-bert</a></b> (π₯22 Β· β 1.9K) - Super easy library for BERT based NLP models. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/utterworks/fast-bert) (π¨βπ» 37 Β· π 340 Β· π 260 - 63% open Β· β±οΈ 19.08.2024):
```
git clone https://github.com/utterworks/fast-bert
```
- [PyPi](https://pypi.org/project/fast-bert) (π₯ 2.5K / month Β· β±οΈ 19.08.2024):
```
pip install fast-bert
```
</details>
<details><summary><b><a href="https://github.com/awslabs/sockeye">Sockeye</a></b> (π₯22 Β· β 1.2K) - Sequence-to-sequence framework with a focus on Neural Machine.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/awslabs/sockeye) (π¨βπ» 60 Β· π 320 Β· π₯ 21 Β· π 310 - 3% open Β· β±οΈ 24.10.2024):
```
git clone https://github.com/awslabs/sockeye
```
- [PyPi](https://pypi.org/project/sockeye) (π₯ 1.8K / month Β· β±οΈ 03.03.2023):
```
pip install sockeye
```
</details>
<details><summary><b><a href="https://github.com/unitaryai/detoxify">detoxify</a></b> (π₯22 Β· β 980) - Trained models & code to predict toxic comments on all 3 Jigsaw.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/unitaryai/detoxify) (π¨βπ» 12 Β· π 120 Β· π₯ 770K Β· π¦ 750 Β· π 66 - 56% open Β· β±οΈ 19.09.2024):
```
git clone https://github.com/unitaryai/detoxify
```
- [PyPi](https://pypi.org/project/detoxify) (π₯ 33K / month Β· π¦ 30 Β· β±οΈ 01.02.2024):
```
pip install detoxify
```
</details>
<details><summary><b><a href="https://github.com/IndicoDataSolutions/finetune">finetune</a></b> (π₯22 Β· β 700) - Scikit-learn style model finetuning for NLP. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/IndicoDataSolutions/finetune) (π¨βπ» 23 Β· π 79 Β· π¦ 13 Β· π 140 - 15% open Β· β±οΈ 23.07.2024):
```
git clone https://github.com/IndicoDataSolutions/finetune
```
- [PyPi](https://pypi.org/project/finetune) (π₯ 660 / month Β· π¦ 2 Β· β±οΈ 29.09.2023):
```
pip install finetune
```
</details>
<details><summary><b><a href="https://github.com/webis-de/small-text">small-text</a></b> (π₯22 Β· β 600) - Active Learning for Text Classification in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/webis-de/small-text) (π¨βπ» 9 Β· π 66 Β· π¦ 33 Β· π 62 - 27% open Β· β±οΈ 24.11.2024):
```
git clone https://github.com/webis-de/small-text
```
- [PyPi](https://pypi.org/project/small-text) (π₯ 780 / month Β· β±οΈ 24.11.2024):
```
pip install small-text
```
- [Conda](https://anaconda.org/conda-forge/small-text) (π₯ 11K Β· β±οΈ 18.08.2024):
```
conda install -c conda-forge small-text
```
</details>
<details><summary><b><a href="https://github.com/EricFillion/happy-transformer">happy-transformer</a></b> (π₯22 Β· β 520 Β· π€) - Happy Transformer makes it easy to fine-tune and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code>huggingface</code></summary>
- [GitHub](https://github.com/EricFillion/happy-transformer) (π¨βπ» 14 Β· π 67 Β· π¦ 300 Β· π 130 - 15% open Β· β±οΈ 19.03.2024):
```
git clone https://github.com/EricFillion/happy-transformer
```
- [PyPi](https://pypi.org/project/happytransformer) (π₯ 2.3K / month Β· π¦ 5 Β· β±οΈ 05.08.2023):
```
pip install happytransformer
```
</details>
<details><summary><b><a href="https://github.com/unum-cloud/uform">UForm</a></b> (π₯19 Β· β 1.1K) - Pocket-Sized Multimodal AI for content understanding and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/unum-cloud/uform) (π¨βπ» 18 Β· π 62 Β· π₯ 490 Β· π¦ 6 Β· π 31 - 29% open Β· β±οΈ 01.10.2024):
```
git clone https://github.com/unum-cloud/uform
```
- [PyPi](https://pypi.org/project/uform) (π₯ 890 / month Β· π¦ 2 Β· β±οΈ 01.10.2024):
```
pip install uform
```
</details>
<details><summary><b><a href="https://github.com/thunlp/OpenNRE">OpenNRE</a></b> (π₯16 Β· β 4.4K Β· π€) - An Open-Source Package for Neural Relation Extraction (NRE). <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/thunlp/OpenNRE) (π¨βπ» 14 Β· π 1.1K Β· π 370 - 4% open Β· β±οΈ 10.01.2024):
```
git clone https://github.com/thunlp/OpenNRE
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/vizseq">VizSeq</a></b> (π₯16 Β· β 440) - An Analysis Toolkit for Natural Language Generation (Translation,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/facebookresearch/vizseq) (π¨βπ» 4 Β· π 61 Β· π¦ 12 Β· π 16 - 43% open Β· β±οΈ 28.09.2024):
```
git clone https://github.com/facebookresearch/vizseq
```
- [PyPi](https://pypi.org/project/vizseq) (π₯ 150 / month Β· β±οΈ 07.08.2020):
```
pip install vizseq
```
</details>
<details><summary>Show 56 hidden projects...</summary>
- <b><a href="https://github.com/allenai/allennlp">AllenNLP</a></b> (π₯36 Β· β 12K Β· π) - An open-source NLP research library, built on PyTorch. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/gunthercox/ChatterBot">ChatterBot</a></b> (π₯34 Β· β 14K Β· π) - ChatterBot is a machine learning, conversational dialog engine.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/facebookresearch/ParlAI">ParlAI</a></b> (π₯32 Β· β 10K Β· π) - A framework for training and evaluating AI models on a variety of.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/seatgeek/fuzzywuzzy">fuzzywuzzy</a></b> (π₯32 Β· β 9.2K Β· π) - Fuzzy String Matching in Python. <code><a href="http://bit.ly/2KucAZR">βοΈGPL-2.0</a></code>
- <b><a href="https://github.com/makcedward/nlpaug">nlpaug</a></b> (π₯29 Β· β 4.5K Β· π) - Data augmentation for NLP. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/dmlc/gluon-nlp">GluonNLP</a></b> (π₯29 Β· β 2.6K Β· π) - Toolkit that enables easy text preprocessing, datasets.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/fastnlp/fastNLP">fastNLP</a></b> (π₯28 Β· β 3.1K Β· π) - fastNLP: A Modularized and Extensible NLP Framework. Currently.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/saffsd/langid.py">langid</a></b> (π₯28 Β· β 2.3K Β· π) - Stand-alone language identification system. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/Ciphey/Ciphey">Ciphey</a></b> (π₯27 Β· β 18K Β· π) - Automatically decrypt encryptions without knowing the key or cipher,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/cjhutto/vaderSentiment">vaderSentiment</a></b> (π₯27 Β· β 4.5K Β· π) - VADER Sentiment Analysis. VADER (Valence Aware Dictionary.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/chartbeat-labs/textacy">textacy</a></b> (π₯27 Β· β 2.2K Β· π) - NLP, before and after spaCy. <code>βUnlicensed</code>
- <b><a href="https://github.com/deepset-ai/FARM">FARM</a></b> (π₯27 Β· β 1.7K Β· π) - Fast & easy transfer learning for NLP. Harvesting language.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/undertheseanlp/underthesea">underthesea</a></b> (π₯27 Β· β 1.4K) - Underthesea - Vietnamese NLP Toolkit. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/vi3k6i5/flashtext">flashtext</a></b> (π₯26 Β· β 5.6K Β· π) - Extract Keywords from sentence or Replace keywords in sentences. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/aboSamoor/polyglot">polyglot</a></b> (π₯26 Β· β 2.3K Β· π) - Multilingual text (NLP) processing toolkit. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/nipunsadvilkar/pySBD">pySBD</a></b> (π₯26 Β· β 820 Β· π) - pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/facebookresearch/pytext">PyText</a></b> (π₯25 Β· β 6.3K Β· π) - A natural language modeling framework based on PyTorch. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/thunlp/OpenPrompt">OpenPrompt</a></b> (π₯25 Β· β 4.4K Β· π) - An Open-Source Framework for Prompt-Learning. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/snipsco/snips-nlu">Snips NLU</a></b> (π₯25 Β· β 3.9K Β· π) - Snips Python library to extract meaning from text. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/huggingface/neuralcoref">neuralcoref</a></b> (π₯25 Β· β 2.9K Β· π) - Fast Coreference Resolution in spaCy with Neural Networks. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/minimaxir/textgenrnn">textgenrnn</a></b> (π₯24 Β· β 4.9K Β· π) - Easily train your own text-generating neural network of any.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/NTMC-Community/MatchZoo">MatchZoo</a></b> (π₯24 Β· β 3.8K Β· π) - Facilitating the design, comparison and sharing of deep.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/bigscience-workshop/promptsource">promptsource</a></b> (π₯24 Β· β 2.7K Β· π) - Toolkit for creating, sharing and using natural language.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/BrikerMan/Kashgari">Kashgari</a></b> (π₯24 Β· β 2.4K Β· π) - Kashgari is a production-level NLP Transfer learning.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/PetrochukM/PyTorch-NLP">pytorch-nlp</a></b> (π₯24 Β· β 2.2K Β· π) - Basic Utilities for PyTorch Natural Language Processing.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/explosion/sense2vec">sense2vec</a></b> (π₯24 Β· β 1.6K Β· π) - Contextually-keyed word vectors. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/nyu-mll/jiant">jiant</a></b> (π₯23 Β· β 1.7K Β· π) - jiant is an nlp toolkit. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/VKCOM/YouTokenToMe">YouTokenToMe</a></b> (π₯23 Β· β 960 Β· π) - Unsupervised text tokenizer focused on computational efficiency. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/mchaput/whoosh">whoosh</a></b> (π₯23 Β· β 590 Β· π) - Pure-Python full-text search library. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">βοΈBSD-1-Clause</a></code>
- <b><a href="https://github.com/minimaxir/gpt-2-simple">gpt-2-simple</a></b> (π₯22 Β· β 3.4K Β· π) - Python package to easily retrain OpenAIs GPT-2 text-.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/IntelLabs/nlp-architect">NLP Architect</a></b> (π₯22 Β· β 2.9K Β· π) - A model library for exploring state-of-the-art deep.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/jbesomi/texthero">Texthero</a></b> (π₯22 Β· β 2.9K Β· π) - Text preprocessing, representation and visualization from zero to.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/asyml/texar">Texar</a></b> (π₯22 Β· β 2.4K Β· π) - Toolkit for Machine Learning, Natural Language Processing, and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/Alir3z4/python-stop-words">stop-words</a></b> (π₯22 Β· β 160 Β· π) - Get list of common stop words in various languages in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/Hironsan/anago">anaGo</a></b> (π₯21 Β· β 1.5K Β· π) - Bidirectional LSTM-CRF and ELMo for Named-Entity Recognition,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/anhaidgroup/deepmatcher">DeepMatcher</a></b> (π₯20 Β· β 5.1K Β· π) - Python package for performing Entity and Text Matching using.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/bytedance/lightseq">lightseq</a></b> (π₯20 Β· β 3.2K Β· π) - LightSeq: A High Performance Library for Sequence Processing.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/Delta-ML/delta">DELTA</a></b> (π₯20 Β· β 1.6K Β· π) - DELTA is a deep learning based natural language and speech.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/textpipe/textpipe">textpipe</a></b> (π₯20 Β· β 300 Β· π) - Textpipe: clean and extract metadata from text. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/jaidevd/numerizer">numerizer</a></b> (π₯20 Β· β 230) - A Python module to convert natural language numerics into ints and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/PKSHATechnology-Research/camphr">Camphr</a></b> (π₯19 Β· β 340 Β· π) - Camphr - NLP libary for creating pipeline components. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code>spacy</code>
- <b><a href="https://github.com/vrasneur/pyfasttext">pyfasttext</a></b> (π₯19 Β· β 230 Β· π) - Yet another Python binding for fastText. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/Franck-Dernoncourt/NeuroNER">NeuroNER</a></b> (π₯18 Β· β 1.7K Β· π) - Named-entity recognition using neural networks. Easy-to-use and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/koursaros-ai/nboost">nboost</a></b> (π₯18 Β· β 680 Β· π) - NBoost is a scalable, search-api-boosting platform for deploying.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/Ki6an/fastT5">fastT5</a></b> (π₯18 Β· β 570 Β· π) - boost inference speed of T5 models by 5x & reduce the model size.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/dsfsi/textaugment">textaugment</a></b> (π₯18 Β· β 410 Β· π) - TextAugment: Text Augmentation Library. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/shaypal5/skift">skift</a></b> (π₯18 Β· β 240 Β· π) - scikit-learn wrappers for Python fastText. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/RUCAIBox/TextBox">TextBox</a></b> (π₯16 Β· β 1.1K Β· π) - TextBox 2.0 is a text generation library with pre-trained language.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/facebookresearch/BLINK">BLINK</a></b> (π₯15 Β· β 1.2K Β· π) - Entity Linker solution. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/pytorch/translate">Translate</a></b> (π₯15 Β· β 830 Β· π) - Translate - a PyTorch Language Library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/victordibia/neuralqa">NeuralQA</a></b> (π₯15 Β· β 230 Β· π) - NeuralQA: A Usable Library for Question Answering on Large Datasets.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/as-ideas/headliner">Headliner</a></b> (π₯15 Β· β 230 Β· π) - Easy training and deployment of seq2seq models. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/abelriboulot/onnxt5">ONNX-T5</a></b> (π₯14 Β· β 250 Β· π) - Summarization, translation, sentiment-analysis, text-generation.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/feedly/transfer-nlp">TransferNLP</a></b> (π₯13 Β· β 290 Β· π) - NLP library designed for reproducible experimentation.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/textvec/textvec">textvec</a></b> (π₯13 Β· β 190 Β· π€) - Text vectorization tool to outperform TFIDF for classification.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/MartinoMensio/spacy-dbpedia-spotlight">spacy-dbpedia-spotlight</a></b> (π₯13 Β· β 110 Β· π) - A spaCy wrapper for DBpedia Spotlight. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code>spacy</code>
</details>
<br>
## Image Data
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for image & video processing, manipulation, and augmentation as well as libraries for computer vision tasks such as facial recognition, object detection, and classification._
<details><summary><b><a href="https://github.com/python-pillow/Pillow">Pillow</a></b> (π₯48 Β· β 12K) - Python Imaging Library (Fork). <code><a href="https://tldrlegal.com/search?q=PIL">βοΈPIL</a></code></summary>
- [GitHub](https://github.com/python-pillow/Pillow) (π¨βπ» 480 Β· π 2.2K Β· π¦ 2M Β· π 3.3K - 4% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/python-pillow/Pillow
```
- [PyPi](https://pypi.org/project/Pillow) (π₯ 130M / month Β· π¦ 8.9K Β· β±οΈ 15.10.2024):
```
pip install Pillow
```
- [Conda](https://anaconda.org/conda-forge/pillow) (π₯ 48M Β· β±οΈ 18.10.2024):
```
conda install -c conda-forge pillow
```
</details>
<details><summary><b><a href="https://github.com/huggingface/pytorch-image-models">PyTorch Image Models</a></b> (π₯42 Β· β 33K) - The largest collection of PyTorch image encoders /.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/huggingface/pytorch-image-models) (π¨βπ» 160 Β· π 4.8K Β· π₯ 7.3M Β· π¦ 43K Β· π 940 - 4% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/rwightman/pytorch-image-models
```
- [PyPi](https://pypi.org/project/timm) (π₯ 5.8M / month Β· π¦ 1K Β· β±οΈ 03.12.2024):
```
pip install timm
```
- [Conda](https://anaconda.org/conda-forge/timm) (π₯ 280K Β· β±οΈ 17.12.2024):
```
conda install -c conda-forge timm
```
</details>
<details><summary><b><a href="https://github.com/pytorch/vision">torchvision</a></b> (π₯41 Β· β 16K) - Datasets, Transforms and Models specific to Computer Vision. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pytorch/vision) (π¨βπ» 620 Β· π 7K Β· π₯ 40K Β· π¦ 21 Β· π 3.5K - 29% open Β· β±οΈ 12.12.2024):
```
git clone https://github.com/pytorch/vision
```
- [PyPi](https://pypi.org/project/torchvision) (π₯ 16M / month Β· π¦ 5.9K Β· β±οΈ 29.10.2024):
```
pip install torchvision
```
- [Conda](https://anaconda.org/conda-forge/torchvision) (π₯ 2M Β· β±οΈ 18.12.2024):
```
conda install -c conda-forge torchvision
```
</details>
<details><summary><b><a href="https://github.com/albumentations-team/albumentations">Albumentations</a></b> (π₯41 Β· β 14K) - Fast and flexible image augmentation library. Paper about.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/albumentations-team/albumentations) (π¨βπ» 160 Β· π 1.7K Β· π¦ 30K Β· π 1.1K - 14% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/albumentations-team/albumentations
```
- [PyPi](https://pypi.org/project/albumentations) (π₯ 5.3M / month Β· π¦ 620 Β· β±οΈ 17.12.2024):
```
pip install albumentations
```
- [Conda](https://anaconda.org/conda-forge/albumentations) (π₯ 220K Β· β±οΈ 22.09.2024):
```
conda install -c conda-forge albumentations
```
</details>
<details><summary><b><a href="https://github.com/Zulko/moviepy">MoviePy</a></b> (π₯41 Β· β 13K) - Video editing with Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/Zulko/moviepy) (π¨βπ» 170 Β· π 1.6K Β· π¦ 51K Β· π 1.6K - 31% open Β· β±οΈ 05.12.2024):
```
git clone https://github.com/Zulko/moviepy
```
- [PyPi](https://pypi.org/project/moviepy) (π₯ 2.3M / month Β· π¦ 1K Β· β±οΈ 25.11.2024):
```
pip install moviepy
```
- [Conda](https://anaconda.org/conda-forge/moviepy) (π₯ 280K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge moviepy
```
</details>
<details><summary><b><a href="https://github.com/serengil/deepface">deepface</a></b> (π₯39 Β· β 15K) - A Lightweight Face Recognition and Facial Attribute Analysis (Age,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/serengil/deepface) (π¨βπ» 73 Β· π 2.2K Β· π¦ 4.9K Β· π 1.1K - 0% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/serengil/deepface
```
- [PyPi](https://pypi.org/project/deepface) (π₯ 320K / month Β· π¦ 44 Β· β±οΈ 17.08.2024):
```
pip install deepface
```
</details>
<details><summary><b><a href="https://github.com/kornia/kornia">Kornia</a></b> (π₯38 Β· β 10K Β· π) - Geometric Computer Vision Library for Spatial AI. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/kornia/kornia) (π¨βπ» 280 Β· π 970 Β· π₯ 1.6K Β· π¦ 13K Β· π 950 - 30% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/kornia/kornia
```
- [PyPi](https://pypi.org/project/kornia) (π₯ 1.7M / month Β· π¦ 290 Β· β±οΈ 05.11.2024):
```
pip install kornia
```
- [Conda](https://anaconda.org/conda-forge/kornia) (π₯ 160K Β· β±οΈ 05.11.2024):
```
conda install -c conda-forge kornia
```
</details>
<details><summary><b><a href="https://github.com/imageio/imageio">imageio</a></b> (π₯38 Β· β 1.5K) - Python library for reading and writing image data. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
- [GitHub](https://github.com/imageio/imageio) (π¨βπ» 120 Β· π 300 Β· π₯ 1.4K Β· π¦ 150K Β· π 610 - 16% open Β· β±οΈ 28.11.2024):
```
git clone https://github.com/imageio/imageio
```
- [PyPi](https://pypi.org/project/imageio) (π₯ 28M / month Β· π¦ 2.5K Β· β±οΈ 28.11.2024):
```
pip install imageio
```
- [Conda](https://anaconda.org/conda-forge/imageio) (π₯ 7.3M Β· β±οΈ 28.11.2024):
```
conda install -c conda-forge imageio
```
</details>
<details><summary><b><a href="https://github.com/deepinsight/insightface">InsightFace</a></b> (π₯37 Β· β 24K) - State-of-the-art 2D and 3D Face Analysis Project. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/deepinsight/insightface) (π¨βπ» 63 Β· π 5.4K Β· π₯ 5.8M Β· π¦ 3.1K Β· π 2.5K - 45% open Β· β±οΈ 05.12.2024):
```
git clone https://github.com/deepinsight/insightface
```
- [PyPi](https://pypi.org/project/insightface) (π₯ 250K / month Β· π¦ 30 Β· β±οΈ 17.12.2022):
```
pip install insightface
```
</details>
<details><summary><b><a href="https://github.com/open-mmlab/mmdetection">MMDetection</a></b> (π₯36 Β· β 30K Β· π€) - OpenMMLab Detection Toolbox and Benchmark. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/open-mmlab/mmdetection) (π¨βπ» 480 Β· π 9.5K Β· π¦ 3.3K Β· π 8.6K - 21% open Β· β±οΈ 05.02.2024):
```
git clone https://github.com/open-mmlab/mmdetection
```
- [PyPi](https://pypi.org/project/mmdet) (π₯ 190K / month Β· π¦ 82 Β· β±οΈ 05.01.2024):
```
pip install mmdet
```
</details>
<details><summary><b><a href="https://github.com/opencv/opencv-python">opencv-python</a></b> (π₯35 Β· β 4.6K) - Automated CI toolchain to produce precompiled opencv-python,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/opencv/opencv-python) (π¨βπ» 49 Β· π 850 Β· π¦ 480K Β· π 830 - 16% open Β· β±οΈ 04.12.2024):
```
git clone https://github.com/opencv/opencv-python
```
- [PyPi](https://pypi.org/project/opencv-python) (π₯ 15M / month Β· π¦ 10K Β· β±οΈ 17.06.2024):
```
pip install opencv-python
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/detectron2">detectron2</a></b> (π₯34 Β· β 31K) - Detectron2 is a platform for object detection, segmentation.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/facebookresearch/detectron2) (π¨βπ» 270 Β· π 7.5K Β· π¦ 2.2K Β· π 3.6K - 14% open Β· β±οΈ 21.11.2024):
```
git clone https://github.com/facebookresearch/detectron2
```
- [PyPi](https://pypi.org/project/detectron2) (π¦ 13 Β· β±οΈ 06.02.2020):
```
pip install detectron2
```
- [Conda](https://anaconda.org/conda-forge/detectron2) (π₯ 500K Β· β±οΈ 06.11.2024):
```
conda install -c conda-forge detectron2
```
</details>
<details><summary><b><a href="https://github.com/PaddlePaddle/PaddleSeg">PaddleSeg</a></b> (π₯34 Β· β 8.8K) - Easy-to-use image segmentation library with awesome pre-.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/PaddlePaddle/PaddleSeg) (π¨βπ» 130 Β· π 1.7K Β· π¦ 1.3K Β· π 2.4K - 9% open Β· β±οΈ 03.12.2024):
```
git clone https://github.com/PaddlePaddle/PaddleSeg
```
- [PyPi](https://pypi.org/project/paddleseg) (π₯ 1.7K / month Β· π¦ 7 Β· β±οΈ 30.11.2022):
```
pip install paddleseg
```
</details>
<details><summary><b><a href="https://github.com/emcconville/wand">Wand</a></b> (π₯34 Β· β 1.4K) - The ctypes-based simple ImageMagick binding for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/emcconville/wand) (π¨βπ» 110 Β· π 200 Β· π₯ 52K Β· π¦ 20K Β· π 430 - 6% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/emcconville/wand
```
- [PyPi](https://pypi.org/project/wand) (π₯ 1.1M / month Β· π¦ 260 Β· β±οΈ 03.11.2023):
```
pip install wand
```
- [Conda](https://anaconda.org/conda-forge/wand) (π₯ 92K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge wand
```
</details>
<details><summary><b><a href="https://github.com/lucidrains/vit-pytorch">vit-pytorch</a></b> (π₯32 Β· β 21K) - Implementation of Vision Transformer, a simple way to achieve.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/lucidrains/vit-pytorch) (π¨βπ» 21 Β· π 3.1K Β· π¦ 560 Β· π 280 - 49% open Β· β±οΈ 24.11.2024):
```
git clone https://github.com/lucidrains/vit-pytorch
```
- [PyPi](https://pypi.org/project/vit-pytorch) (π₯ 28K / month Β· π¦ 17 Β· β±οΈ 24.11.2024):
```
pip install vit-pytorch
```
</details>
<details><summary><b><a href="https://github.com/lightly-ai/lightly">lightly</a></b> (π₯32 Β· β 3.2K) - A python library for self-supervised learning on images. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/lightly-ai/lightly) (π¨βπ» 60 Β· π 280 Β· π¦ 360 Β· π 590 - 12% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/lightly-ai/lightly
```
- [PyPi](https://pypi.org/project/lightly) (π₯ 57K / month Β· π¦ 17 Β· β±οΈ 29.11.2024):
```
pip install lightly
```
</details>
<details><summary><b><a href="https://github.com/JohannesBuchner/imagehash">ImageHash</a></b> (π₯31 Β· β 3.4K) - A Python Perceptual Image Hashing Module. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
- [GitHub](https://github.com/JohannesBuchner/imagehash) (π¨βπ» 27 Β· π 340 Β· π¦ 15K Β· π 140 - 13% open Β· β±οΈ 09.10.2024):
```
git clone https://github.com/JohannesBuchner/imagehash
```
- [PyPi](https://pypi.org/project/ImageHash) (π₯ 1.5M / month Β· π¦ 240 Β· β±οΈ 28.09.2022):
```
pip install ImageHash
```
- [Conda](https://anaconda.org/conda-forge/imagehash) (π₯ 410K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge imagehash
```
</details>
<details><summary><b><a href="https://github.com/PaddlePaddle/PaddleDetection">PaddleDetection</a></b> (π₯30 Β· β 13K) - Object Detection toolkit based on PaddlePaddle. It.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/PaddlePaddle/PaddleDetection) (π¨βπ» 180 Β· π 2.9K Β· π 5.5K - 22% open Β· β±οΈ 03.12.2024):
```
git clone https://github.com/PaddlePaddle/PaddleDetection
```
- [PyPi](https://pypi.org/project/paddledet) (π₯ 600 / month Β· π¦ 2 Β· β±οΈ 19.09.2022):
```
pip install paddledet
```
</details>
<details><summary><b><a href="https://github.com/OlafenwaMoses/ImageAI">imageai</a></b> (π₯30 Β· β 8.7K Β· π€) - A python library built to empower developers to build applications.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/OlafenwaMoses/ImageAI) (π¨βπ» 19 Β· π 2.2K Β· π₯ 950K Β· π¦ 1.7K Β· π 760 - 41% open Β· β±οΈ 20.02.2024):
```
git clone https://github.com/OlafenwaMoses/ImageAI
```
- [PyPi](https://pypi.org/project/imageai) (π₯ 12K / month Β· π¦ 19 Β· β±οΈ 02.01.2023):
```
pip install imageai
```
- [Conda](https://anaconda.org/conda-forge/imageai) (π₯ 8.4K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge imageai
```
</details>
<details><summary><b><a href="https://github.com/mindee/doctr">doctr</a></b> (π₯30 Β· β 4K) - docTR (Document Text Recognition) - a seamless, high-.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/mindee/doctr) (π¨βπ» 55 Β· π 440 Β· π₯ 4.5M Β· π 380 - 7% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/mindee/doctr
```
- [PyPi](https://pypi.org/project/python-doctr) (π₯ 41K / month Β· π¦ 12 Β· β±οΈ 21.10.2024):
```
pip install python-doctr
```
</details>
<details><summary><b><a href="https://github.com/CellProfiler/CellProfiler">CellProfiler</a></b> (π₯30 Β· β 930) - An open-source application for biological image analysis. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/CellProfiler/CellProfiler) (π¨βπ» 140 Β· π 380 Β· π₯ 8.2K Β· π¦ 26 Β· π 3.3K - 9% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/CellProfiler/CellProfiler
```
- [PyPi](https://pypi.org/project/cellprofiler) (π₯ 1.3K / month Β· π¦ 2 Β· β±οΈ 16.09.2024):
```
pip install cellprofiler
```
</details>
<details><summary><b><a href="https://github.com/obss/sahi">sahi</a></b> (π₯29 Β· β 4.2K) - Framework agnostic sliced/tiled inference + interactive ui + error analysis.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/obss/sahi) (π¨βπ» 48 Β· π 600 Β· π₯ 30K Β· π¦ 1.5K Β· β±οΈ 18.12.2024):
```
git clone https://github.com/obss/sahi
```
- [PyPi](https://pypi.org/project/sahi) (π₯ 160K / month Β· π¦ 31 Β· β±οΈ 16.12.2024):
```
pip install sahi
```
- [Conda](https://anaconda.org/conda-forge/sahi) (π₯ 82K Β· β±οΈ 18.12.2024):
```
conda install -c conda-forge sahi
```
</details>
<details><summary><b><a href="https://github.com/ipazc/mtcnn">mtcnn</a></b> (π₯29 Β· β 2.3K) - MTCNN face detection implementation for TensorFlow, as a PIP package. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/ipazc/mtcnn) (π¨βπ» 16 Β· π 530 Β· π₯ 16 Β· π¦ 6.8K Β· π 130 - 37% open Β· β±οΈ 08.10.2024):
```
git clone https://github.com/ipazc/mtcnn
```
- [PyPi](https://pypi.org/project/mtcnn) (π₯ 150K / month Β· π¦ 73 Β· β±οΈ 08.10.2024):
```
pip install mtcnn
```
- [Conda](https://anaconda.org/conda-forge/mtcnn) (π₯ 14K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge mtcnn
```
</details>
<details><summary><b><a href="https://github.com/luispedro/mahotas">mahotas</a></b> (π₯28 Β· β 860) - Computer Vision in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/luispedro/mahotas) (π¨βπ» 35 Β· π 150 Β· π¦ 1.4K Β· π 91 - 23% open Β· β±οΈ 17.07.2024):
```
git clone https://github.com/luispedro/mahotas
```
- [PyPi](https://pypi.org/project/mahotas) (π₯ 23K / month Β· π¦ 63 Β· β±οΈ 17.07.2024):
```
pip install mahotas
```
- [Conda](https://anaconda.org/conda-forge/mahotas) (π₯ 530K Β· β±οΈ 18.07.2024):
```
conda install -c conda-forge mahotas
```
</details>
<details><summary><b><a href="https://github.com/1adrianb/face-alignment">Face Alignment</a></b> (π₯27 Β· β 7.1K) - 2D and 3D Face alignment library build using pytorch. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/1adrianb/face-alignment) (π¨βπ» 26 Β· π 1.4K Β· π¦ 21 Β· π 320 - 24% open Β· β±οΈ 30.08.2024):
```
git clone https://github.com/1adrianb/face-alignment
```
- [PyPi](https://pypi.org/project/face-alignment) (π₯ 42K / month Β· π¦ 10 Β· β±οΈ 17.08.2023):
```
pip install face-alignment
```
</details>
<details><summary><b><a href="https://github.com/timesler/facenet-pytorch">facenet-pytorch</a></b> (π₯27 Β· β 4.6K) - Pretrained Pytorch face detection (MTCNN) and facial.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/timesler/facenet-pytorch) (π¨βπ» 18 Β· π 940 Β· π₯ 1.5M Β· π¦ 2.6K Β· π 180 - 41% open Β· β±οΈ 02.08.2024):
```
git clone https://github.com/timesler/facenet-pytorch
```
- [PyPi](https://pypi.org/project/facenet-pytorch) (π₯ 83K / month Β· π¦ 51 Β· β±οΈ 29.04.2024):
```
pip install facenet-pytorch
```
</details>
<details><summary><b><a href="https://github.com/abhiTronix/vidgear">vidgear</a></b> (π₯27 Β· β 3.4K) - A High-performance cross-platform Video Processing Python framework.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/abhiTronix/vidgear) (π¨βπ» 14 Β· π 250 Β· π₯ 2K Β· π¦ 650 Β· π 300 - 2% open Β· β±οΈ 22.06.2024):
```
git clone https://github.com/abhiTronix/vidgear
```
- [PyPi](https://pypi.org/project/vidgear) (π₯ 20K / month Β· π¦ 15 Β· β±οΈ 22.06.2024):
```
pip install vidgear
```
</details>
<details><summary><b><a href="https://github.com/tryolabs/norfair">Norfair</a></b> (π₯26 Β· β 2.4K) - Lightweight Python library for adding real-time multi-object tracking.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/tryolabs/norfair) (π¨βπ» 31 Β· π 250 Β· π₯ 340 Β· π¦ 250 Β· π 170 - 14% open Β· β±οΈ 27.07.2024):
```
git clone https://github.com/tryolabs/norfair
```
- [PyPi](https://pypi.org/project/norfair) (π₯ 22K / month Β· π¦ 9 Β· β±οΈ 30.05.2022):
```
pip install norfair
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/pytorchvideo">pytorchvideo</a></b> (π₯25 Β· β 3.4K) - A deep learning library for video understanding research. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/facebookresearch/pytorchvideo) (π¨βπ» 57 Β· π 410 Β· π 210 - 50% open Β· β±οΈ 26.11.2024):
```
git clone https://github.com/facebookresearch/pytorchvideo
```
- [PyPi](https://pypi.org/project/pytorchvideo) (π₯ 31K / month Β· π¦ 24 Β· β±οΈ 20.01.2022):
```
pip install pytorchvideo
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/graphics">tensorflow-graphics</a></b> (π₯25 Β· β 2.8K) - TensorFlow Graphics: Differentiable Graphics Layers.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/graphics) (π¨βπ» 39 Β· π 370 Β· π 240 - 60% open Β· β±οΈ 01.08.2024):
```
git clone https://github.com/tensorflow/graphics
```
- [PyPi](https://pypi.org/project/tensorflow-graphics) (π₯ 18K / month Β· π¦ 11 Β· β±οΈ 03.12.2021):
```
pip install tensorflow-graphics
```
</details>
<details><summary><b><a href="https://github.com/google-research/kubric">kubric</a></b> (π₯25 Β· β 2.4K) - A data generation pipeline for creating semi-realistic synthetic.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/google-research/kubric) (π¨βπ» 31 Β· π 230 Β· π¦ 7 Β· π 190 - 33% open Β· β±οΈ 29.11.2024):
```
git clone https://github.com/google-research/kubric
```
- [PyPi](https://pypi.org/project/kubric-nightly) (π₯ 11K / month Β· β±οΈ 27.12.2023):
```
pip install kubric-nightly
```
</details>
<details><summary><b><a href="https://github.com/libvips/pyvips">pyvips</a></b> (π₯25 Β· β 660) - python binding for libvips using cffi. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/libvips/pyvips) (π¨βπ» 16 Β· π 50 Β· π¦ 860 Β· π 450 - 42% open Β· β±οΈ 29.10.2024):
```
git clone https://github.com/libvips/pyvips
```
- [PyPi](https://pypi.org/project/pyvips) (π₯ 56K / month Β· π¦ 77 Β· β±οΈ 28.04.2024):
```
pip install pyvips
```
- [Conda](https://anaconda.org/conda-forge/pyvips) (π₯ 150K Β· β±οΈ 06.09.2024):
```
conda install -c conda-forge pyvips
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/mmf">MMF</a></b> (π₯24 Β· β 5.5K) - A modular framework for vision & language multimodal research from.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/facebookresearch/mmf) (π¨βπ» 120 Β· π 920 Β· π¦ 21 Β· π 690 - 21% open Β· β±οΈ 15.11.2024):
```
git clone https://github.com/facebookresearch/mmf
```
- [PyPi](https://pypi.org/project/mmf) (π₯ 640 / month Β· π¦ 1 Β· β±οΈ 12.06.2020):
```
pip install mmf
```
</details>
<details><summary><b><a href="https://github.com/idealo/imagededup">Image Deduplicator</a></b> (π₯24 Β· β 5.2K) - Finding duplicate images made easy!. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/idealo/imagededup) (π¨βπ» 16 Β· π 450 Β· π¦ 160 Β· π 130 - 30% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/idealo/imagededup
```
- [PyPi](https://pypi.org/project/imagededup) (π₯ 19K / month Β· π¦ 5 Β· β±οΈ 28.04.2023):
```
pip install imagededup
```
</details>
<details><summary><b><a href="https://github.com/qubvel/segmentation_models">segmentation_models</a></b> (π₯24 Β· β 4.8K) - Segmentation models with pretrained backbones. Keras.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/qubvel/segmentation_models) (π¨βπ» 15 Β· π 1K Β· π 540 - 50% open Β· β±οΈ 21.08.2024):
```
git clone https://github.com/qubvel/segmentation_models
```
- [PyPi](https://pypi.org/project/segmentation_models) (π₯ 34K / month Β· π¦ 28 Β· β±οΈ 10.01.2020):
```
pip install segmentation_models
```
</details>
<details><summary><b><a href="https://github.com/libffcv/ffcv">ffcv</a></b> (π₯24 Β· β 2.9K Β· π€) - FFCV: Fast Forward Computer Vision (and other ML workloads!). <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/libffcv/ffcv) (π¨βπ» 31 Β· π 180 Β· π¦ 57 Β· π 290 - 38% open Β· β±οΈ 06.05.2024):
```
git clone https://github.com/libffcv/ffcv
```
- [PyPi](https://pypi.org/project/ffcv) (π₯ 810 / month Β· π¦ 1 Β· β±οΈ 28.01.2022):
```
pip install ffcv
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/vissl">vissl</a></b> (π₯22 Β· β 3.3K Β· π€) - VISSL is FAIRs library of extensible, modular and scalable.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/facebookresearch/vissl) (π¨βπ» 38 Β· π 330 Β· π¦ 57 Β· π 190 - 43% open Β· β±οΈ 03.03.2024):
```
git clone https://github.com/facebookresearch/vissl
```
- [PyPi](https://pypi.org/project/vissl) (π₯ 130 / month Β· π¦ 1 Β· β±οΈ 02.11.2021):
```
pip install vissl
```
</details>
<details><summary><b><a href="https://github.com/airctic/icevision">icevision</a></b> (π₯22 Β· β 850) - An Agnostic Computer Vision Framework - Pluggable to any Training.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/airctic/icevision) (π¨βπ» 41 Β· π 130 Β· π 570 - 10% open Β· β±οΈ 31.10.2024):
```
git clone https://github.com/airctic/icevision
```
- [PyPi](https://pypi.org/project/icevision) (π₯ 2.9K / month Β· π¦ 6 Β· β±οΈ 10.02.2022):
```
pip install icevision
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/detr">DEβ«ΆTR</a></b> (π₯21 Β· β 14K Β· π€) - End-to-End Object Detection with Transformers. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/facebookresearch/detr) (π¨βπ» 27 Β· π 2.4K Β· π¦ 21 Β· π 540 - 47% open Β· β±οΈ 12.03.2024):
```
git clone https://github.com/facebookresearch/detr
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/SlowFast">PySlowFast</a></b> (π₯21 Β· β 6.7K) - PySlowFast: video understanding codebase from FAIR for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/facebookresearch/SlowFast) (π¨βπ» 34 Β· π 1.2K Β· π¦ 22 Β· π 700 - 58% open Β· β±οΈ 26.11.2024):
```
git clone https://github.com/facebookresearch/SlowFast
```
- [PyPi](https://pypi.org/project/pyslowfast) (π₯ 47 / month Β· β±οΈ 15.01.2020):
```
pip install pyslowfast
```
</details>
<details><summary><b><a href="https://github.com/idealo/image-super-resolution">Image Super-Resolution</a></b> (π₯21 Β· β 4.7K) - Super-scale your images and run experiments with.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/idealo/image-super-resolution) (π¨βπ» 11 Β· π 750 Β· π 220 - 48% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/idealo/image-super-resolution
```
- [PyPi](https://pypi.org/project/ISR) (π₯ 5.8K / month Β· π¦ 5 Β· β±οΈ 08.01.2020):
```
pip install ISR
```
- [Docker Hub](https://hub.docker.com/r/idealo/image-super-resolution-gpu) (π₯ 250 Β· β 1 Β· β±οΈ 01.04.2019):
```
docker pull idealo/image-super-resolution-gpu
```
</details>
<details><summary><b><a href="https://github.com/google-research/scenic">scenic</a></b> (π₯18 Β· β 3.4K) - Scenic: A Jax Library for Computer Vision Research and Beyond. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/google-research/scenic) (π¨βπ» 90 Β· π 440 Β· π 270 - 55% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/google-research/scenic
```
</details>
<details><summary>Show 22 hidden projects...</summary>
- <b><a href="https://github.com/scikit-image/scikit-image">scikit-image</a></b> (π₯42 Β· β 6.1K Β· π) - Image processing in Python. <code>βUnlicensed</code>
- <b><a href="https://github.com/glfw/glfw">glfw</a></b> (π₯37 Β· β 13K) - A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input. <code><a href="https://tldrlegal.com/search?q=Zlib">βοΈZlib</a></code>
- <b><a href="https://github.com/aleju/imgaug">imgaug</a></b> (π₯36 Β· β 14K Β· π) - Image augmentation for machine learning experiments. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/ageitgey/face_recognition">Face Recognition</a></b> (π₯35 Β· β 54K Β· π) - The worlds simplest facial recognition api for Python.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/facebookresearch/pytorch3d">PyTorch3D</a></b> (π₯34 Β· β 8.9K) - PyTorch3D is FAIRs library of reusable components for.. <code>βUnlicensed</code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/PyImageSearch/imutils">imutils</a></b> (π₯31 Β· β 4.5K Β· π) - A series of convenience functions to make basic image processing.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/dmlc/gluon-cv">GluonCV</a></b> (π₯30 Β· β 5.9K Β· π) - Gluon CV Toolkit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/Layout-Parser/layout-parser">layout-parser</a></b> (π₯28 Β· β 5K Β· π) - A Unified Toolkit for Deep Learning Based Document Image.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/mdbloice/Augmentor">Augmentor</a></b> (π₯27 Β· β 5.1K Β· π) - Image augmentation library in Python for machine learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/chainer/chainercv">chainercv</a></b> (π₯27 Β· β 1.5K Β· π) - ChainerCV: a Library for Deep Learning in Computer Vision. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/uploadcare/pillow-simd">Pillow-SIMD</a></b> (π₯25 Β· β 2.2K) - The friendly PIL fork. <code><a href="https://tldrlegal.com/search?q=PIL">βοΈPIL</a></code>
- <b><a href="https://github.com/lucidrains/deep-daze">deep-daze</a></b> (π₯23 Β· β 4.4K Β· π) - Simple command line tool for text to image generation using.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/tryolabs/luminoth">Luminoth</a></b> (π₯23 Β· β 2.4K Β· π) - Deep Learning toolkit for Computer Vision. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/facebookresearch/ClassyVision">Classy Vision</a></b> (π₯22 Β· β 1.6K Β· π) - An end-to-end PyTorch framework for image and video.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/rhsimplex/image-match">image-match</a></b> (π₯20 Β· β 2.9K Β· π) - Quickly search over billions of images. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/hhatto/nude.py">nude.py</a></b> (π₯20 Β· β 920 Β· π) - Nudity detection with Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/alankbi/detecto">detecto</a></b> (π₯20 Β· β 620 Β· π) - Build fully-functioning computer vision models with PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/facebookresearch/pycls">pycls</a></b> (π₯18 Β· β 2.1K Β· π) - Codebase for Image Classification Research, written in PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/imedslab/solt">solt</a></b> (π₯18 Β· β 260) - Streaming over lightweight data transformations. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/jasmcaus/caer">Caer</a></b> (π₯17 Β· β 780 Β· π) - A lightweight Computer Vision library. Scale your models, not boilerplate. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/nicolas-chaulet/torch-points3d">Torch Points 3D</a></b> (π₯16 Β· β 220 Β· π) - Pytorch framework for doing deep learning on point.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/qanastek/HugsVision">HugsVision</a></b> (π₯16 Β· β 200 Β· π) - HugsVision is a easy to use huggingface wrapper for state-of-.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code>huggingface</code>
</details>
<br>
## Graph Data
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for graph processing, clustering, embedding, and machine learning tasks._
<details><summary><b><a href="https://github.com/networkx/networkx">networkx</a></b> (π₯44 Β· β 15K) - Network Analysis in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/networkx/networkx) (π¨βπ» 760 Β· π 3.3K Β· π₯ 76 Β· π¦ 330K Β· π 3.4K - 10% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/networkx/networkx
```
- [PyPi](https://pypi.org/project/networkx) (π₯ 69M / month Β· π¦ 9.6K Β· β±οΈ 21.10.2024):
```
pip install networkx
```
- [Conda](https://anaconda.org/conda-forge/networkx) (π₯ 19M Β· β±οΈ 13.11.2024):
```
conda install -c conda-forge networkx
```
</details>
<details><summary><b><a href="https://github.com/pyg-team/pytorch_geometric">PyTorch Geometric</a></b> (π₯41 Β· β 22K) - Graph Neural Network Library for PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pyg-team/pytorch_geometric) (π¨βπ» 530 Β· π 3.7K Β· π¦ 7.3K Β· π 3.8K - 29% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/pyg-team/pytorch_geometric
```
- [PyPi](https://pypi.org/project/torch-geometric) (π₯ 490K / month Β· π¦ 360 Β· β±οΈ 26.09.2024):
```
pip install torch-geometric
```
- [Conda](https://anaconda.org/conda-forge/pytorch_geometric) (π₯ 130K Β· β±οΈ 19.12.2024):
```
conda install -c conda-forge pytorch_geometric
```
</details>
<details><summary><b><a href="https://github.com/dmlc/dgl">dgl</a></b> (π₯37 Β· β 14K Β· π) - Python package built to ease deep learning on graph, on top of.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/dmlc/dgl) (π¨βπ» 300 Β· π 3K Β· π¦ 320 Β· π 2.9K - 18% open Β· β±οΈ 18.10.2024):
```
git clone https://github.com/dmlc/dgl
```
- [PyPi](https://pypi.org/project/dgl) (π₯ 880K / month Β· π¦ 150 Β· β±οΈ 13.05.2024):
```
pip install dgl
```
</details>
<details><summary><b><a href="https://github.com/graphistry/pygraphistry">pygraphistry</a></b> (π₯32 Β· β 2.2K) - PyGraphistry is a Python library to quickly load, shape,.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/graphistry/pygraphistry) (π¨βπ» 45 Β· π 210 Β· π¦ 130 Β· π 340 - 52% open Β· β±οΈ 13.12.2024):
```
git clone https://github.com/graphistry/pygraphistry
```
- [PyPi](https://pypi.org/project/graphistry) (π₯ 18K / month Β· π¦ 6 Β· β±οΈ 13.12.2024):
```
pip install graphistry
```
</details>
<details><summary><b><a href="https://github.com/pykeen/pykeen">PyKEEN</a></b> (π₯31 Β· β 1.7K) - A Python library for learning and evaluating knowledge graph embeddings. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/pykeen/pykeen) (π¨βπ» 41 Β· π 190 Β· π₯ 230 Β· π¦ 260 Β· π 580 - 19% open Β· β±οΈ 10.11.2024):
```
git clone https://github.com/pykeen/pykeen
```
- [PyPi](https://pypi.org/project/pykeen) (π₯ 15K / month Β· π¦ 19 Β· β±οΈ 29.10.2024):
```
pip install pykeen
```
</details>
<details><summary><b><a href="https://github.com/danielegrattarola/spektral">Spektral</a></b> (π₯28 Β· β 2.4K Β· π€) - Graph Neural Networks with Keras and Tensorflow 2. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/danielegrattarola/spektral) (π¨βπ» 27 Β· π 340 Β· π¦ 360 Β· π 280 - 25% open Β· β±οΈ 21.01.2024):
```
git clone https://github.com/danielegrattarola/spektral
```
- [PyPi](https://pypi.org/project/spektral) (π₯ 9.9K / month Β· π¦ 7 Β· β±οΈ 21.01.2024):
```
pip install spektral
```
</details>
<details><summary><b><a href="https://github.com/snap-stanford/ogb">ogb</a></b> (π₯28 Β· β 2K) - Benchmark datasets, data loaders, and evaluators for graph machine learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/snap-stanford/ogb) (π¨βπ» 32 Β· π 400 Β· π¦ 2.1K Β· π 300 - 9% open Β· β±οΈ 09.12.2024):
```
git clone https://github.com/snap-stanford/ogb
```
- [PyPi](https://pypi.org/project/ogb) (π₯ 43K / month Β· π¦ 22 Β· β±οΈ 02.11.2022):
```
pip install ogb
```
- [Conda](https://anaconda.org/conda-forge/ogb) (π₯ 43K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge ogb
```
</details>
<details><summary><b><a href="https://github.com/Accenture/AmpliGraph">AmpliGraph</a></b> (π₯27 Β· β 2.2K Β· π€) - Python library for Representation Learning on Knowledge.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/Accenture/AmpliGraph) (π¨βπ» 21 Β· π 250 Β· π¦ 58 Β· π 230 - 13% open Β· β±οΈ 28.02.2024):
```
git clone https://github.com/Accenture/AmpliGraph
```
- [PyPi](https://pypi.org/project/ampligraph) (π₯ 1.5K / month Β· π¦ 2 Β· β±οΈ 26.02.2024):
```
pip install ampligraph
```
</details>
<details><summary><b><a href="https://github.com/benedekrozemberczki/pytorch_geometric_temporal">pytorch_geometric_temporal</a></b> (π₯25 Β· β 2.7K) - PyTorch Geometric Temporal: Spatiotemporal Signal.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/benedekrozemberczki/pytorch_geometric_temporal) (π¨βπ» 34 Β· π 370 Β· π 200 - 20% open Β· β±οΈ 14.10.2024):
```
git clone https://github.com/benedekrozemberczki/pytorch_geometric_temporal
```
- [PyPi](https://pypi.org/project/torch-geometric-temporal) (π₯ 3K / month Β· π¦ 7 Β· β±οΈ 04.09.2022):
```
pip install torch-geometric-temporal
```
</details>
<details><summary><b><a href="https://github.com/eliorc/node2vec">Node2Vec</a></b> (π₯24 Β· β 1.3K) - Implementation of the node2vec algorithm. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/eliorc/node2vec) (π¨βπ» 16 Β· π 250 Β· π¦ 740 Β· π 93 - 5% open Β· β±οΈ 02.08.2024):
```
git clone https://github.com/eliorc/node2vec
```
- [PyPi](https://pypi.org/project/node2vec) (π₯ 21K / month Β· π¦ 31 Β· β±οΈ 02.08.2024):
```
pip install node2vec
```
- [Conda](https://anaconda.org/conda-forge/node2vec) (π₯ 32K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge node2vec
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/PyTorch-BigGraph">PyTorch-BigGraph</a></b> (π₯23 Β· β 3.4K Β· π€) - Generate embeddings from large-scale graph-structured.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/facebookresearch/PyTorch-BigGraph) (π¨βπ» 32 Β· π 450 Β· π₯ 220 Β· π 200 - 32% open Β· β±οΈ 03.03.2024):
```
git clone https://github.com/facebookresearch/PyTorch-BigGraph
```
- [PyPi](https://pypi.org/project/torchbiggraph) (π₯ 280K / month Β· π¦ 2 Β· β±οΈ 14.10.2019):
```
pip install torchbiggraph
```
</details>
<details><summary><b><a href="https://github.com/rusty1s/pytorch_cluster">torch-cluster</a></b> (π₯23 Β· β 840) - PyTorch Extension Library of Optimized Graph Cluster.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/rusty1s/pytorch_cluster) (π¨βπ» 36 Β· π 150 Β· π 180 - 19% open Β· β±οΈ 14.11.2024):
```
git clone https://github.com/rusty1s/pytorch_cluster
```
- [PyPi](https://pypi.org/project/torch-cluster) (π₯ 16K / month Β· π¦ 62 Β· β±οΈ 12.10.2023):
```
pip install torch-cluster
```
- [Conda](https://anaconda.org/conda-forge/pytorch_cluster) (π₯ 240K Β· β±οΈ 28.08.2024):
```
conda install -c conda-forge pytorch_cluster
```
</details>
<details><summary><b><a href="https://github.com/THUMNLab/AutoGL">AutoGL</a></b> (π₯15 Β· β 1.1K Β· π€) - An autoML framework & toolkit for machine learning on graphs. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/THUMNLab/AutoGL) (π¨βπ» 16 Β· π 120 Β· π 39 - 35% open Β· β±οΈ 05.02.2024):
```
git clone https://github.com/THUMNLab/AutoGL
```
- [PyPi](https://pypi.org/project/auto-graph-learning) (β±οΈ 23.12.2020):
```
pip install auto-graph-learning
```
</details>
<details><summary><b><a href="https://github.com/thunlp/OpenNE">OpenNE</a></b> (π₯14 Β· β 1.7K Β· π€) - An Open-Source Package for Network Embedding (NE). <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/thunlp/OpenNE) (π¨βπ» 12 Β· π 490 Β· π 110 - 9% open Β· β±οΈ 10.01.2024):
```
git clone https://github.com/thunlp/OpenNE
```
</details>
<details><summary><b><a href="https://github.com/DeepGraphLearning/graphvite">GraphVite</a></b> (π₯14 Β· β 1.2K) - GraphVite: A General and High-performance Graph Embedding System. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/DeepGraphLearning/graphvite) (π¨βπ» 1 Β· π 150 Β· π 110 - 46% open Β· β±οΈ 14.06.2024):
```
git clone https://github.com/DeepGraphLearning/graphvite
```
- [Conda](https://anaconda.org/milagraph/graphvite) (π₯ 5K Β· β±οΈ 16.06.2023):
```
conda install -c milagraph graphvite
```
</details>
<details><summary>Show 21 hidden projects...</summary>
- <b><a href="https://github.com/igraph/python-igraph">igraph</a></b> (π₯34 Β· β 1.3K) - Python interface for igraph. <code><a href="http://bit.ly/2KucAZR">βοΈGPL-2.0</a></code>
- <b><a href="https://github.com/stellargraph/stellargraph">StellarGraph</a></b> (π₯27 Β· β 3K Β· π) - StellarGraph - Machine Learning on Graphs. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/Kozea/pygal">pygal</a></b> (π₯27 Β· β 2.7K) - PYthon svg GrAph plotting Library. <code><a href="http://bit.ly/37RvQcA">βοΈLGPL-3.0</a></code>
- <b><a href="https://github.com/PaddlePaddle/PGL">Paddle Graph Learning</a></b> (π₯26 Β· β 1.6K Β· π) - Paddle Graph Learning (PGL) is an efficient and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/benedekrozemberczki/karateclub">Karate Club</a></b> (π₯23 Β· β 2.2K) - Karate Club: An API Oriented Open-source Python Framework for.. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/graph4ai/graph4nlp">graph4nlp</a></b> (π₯22 Β· β 1.7K Β· π) - Graph4nlp is the library for the easy use of Graph.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/google-deepmind/jraph">jraph</a></b> (π₯22 Β· β 1.4K Β· π) - A Graph Neural Network Library in Jax. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/google-deepmind/graph_nets">graph-nets</a></b> (π₯21 Β· β 5.4K Β· π) - Build Graph Nets in Tensorflow. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/predict-idlab/pyRDF2Vec">pyRDF2Vec</a></b> (π₯21 Β· β 250 Β· π) - Python Implementation and Extension of RDF2Vec. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/phanein/deepwalk">DeepWalk</a></b> (π₯20 Β· β 2.7K Β· π) - DeepWalk - Deep Learning for Graphs. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/divelab/DIG">DIG</a></b> (π₯20 Β· β 1.9K Β· π€) - A library for graph deep learning research. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/snap-stanford/deepsnap">deepsnap</a></b> (π₯20 Β· β 550 Β· π) - Python library assists deep learning on graphs. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/snap-stanford/GraphGym">GraphGym</a></b> (π₯19 Β· β 1.7K Β· π) - Platform for designing and evaluating Graph Neural Networks (GNN). <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/deepgraph/deepgraph">DeepGraph</a></b> (π₯18 Β· β 290 Β· π€) - Analyze Data with Pandas-based Networks. Documentation:. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/gsi-upm/sematch">Sematch</a></b> (π₯17 Β· β 430 Β· π) - semantic similarity framework for knowledge graph. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/alibaba/euler">Euler</a></b> (π₯16 Β· β 2.9K Β· π) - A distributed graph deep learning framework. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/typedb/typedb-ml">kglib</a></b> (π₯16 Β· β 550 Β· π) - TypeDB-ML is the Machine Learning integrations library for TypeDB. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/microsoft/ptgnn">ptgnn</a></b> (π₯15 Β· β 380 Β· π) - A PyTorch Graph Neural Network Library. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/shenweichen/GraphEmbedding">GraphEmbedding</a></b> (π₯14 Β· β 3.7K Β· π) - Implementation and experiments of graph embedding.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/williamleif/GraphSAGE">GraphSAGE</a></b> (π₯14 Β· β 3.4K Β· π) - Representation learning on large graphs using stochastic.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/thunlp/OpenKE">OpenKE</a></b> (π₯13 Β· β 3.9K Β· π€) - An Open-Source Package for Knowledge Embedding (KE). <code>βUnlicensed</code>
</details>
<br>
## Audio Data
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for audio analysis, manipulation, transformation, and extraction, as well as speech recognition and music generation tasks._
<details><summary><b><a href="https://github.com/speechbrain/speechbrain">speechbrain</a></b> (π₯39 Β· β 9.1K) - A PyTorch-based Speech Toolkit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/speechbrain/speechbrain) (π¨βπ» 250 Β· π 1.4K Β· π¦ 2.6K Β· π 1.2K - 12% open Β· β±οΈ 09.12.2024):
```
git clone https://github.com/speechbrain/speechbrain
```
- [PyPi](https://pypi.org/project/speechbrain) (π₯ 2.6M / month Β· π¦ 67 Β· β±οΈ 30.10.2024):
```
pip install speechbrain
```
</details>
<details><summary><b><a href="https://github.com/espnet/espnet">espnet</a></b> (π₯38 Β· β 8.6K) - End-to-End Speech Processing Toolkit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/espnet/espnet) (π¨βπ» 470 Β· π 2.2K Β· π₯ 83 Β· π¦ 400 Β· π 2.5K - 14% open Β· β±οΈ 08.12.2024):
```
git clone https://github.com/espnet/espnet
```
- [PyPi](https://pypi.org/project/espnet) (π₯ 22K / month Β· π¦ 12 Β· β±οΈ 04.12.2024):
```
pip install espnet
```
</details>
<details><summary><b><a href="https://github.com/Uberi/speech_recognition">SpeechRecognition</a></b> (π₯36 Β· β 8.5K) - Speech recognition module for Python, supporting several.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/Uberi/speech_recognition) (π¨βπ» 53 Β· π 2.4K Β· π¦ 21 Β· π 670 - 50% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/Uberi/speech_recognition
```
- [PyPi](https://pypi.org/project/SpeechRecognition) (π₯ 1M / month Β· π¦ 610 Β· β±οΈ 08.12.2024):
```
pip install SpeechRecognition
```
- [Conda](https://anaconda.org/conda-forge/speechrecognition) (π₯ 210K Β· β±οΈ 09.12.2024):
```
conda install -c conda-forge speechrecognition
```
</details>
<details><summary><b><a href="https://github.com/pytorch/audio">torchaudio</a></b> (π₯35 Β· β 2.6K) - Data manipulation and transformation for audio signal.. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pytorch/audio) (π¨βπ» 230 Β· π 660 Β· π 990 - 26% open Β· β±οΈ 14.12.2024):
```
git clone https://github.com/pytorch/audio
```
- [PyPi](https://pypi.org/project/torchaudio) (π₯ 5.3M / month Β· π¦ 1.4K Β· β±οΈ 29.10.2024):
```
pip install torchaudio
```
</details>
<details><summary><b><a href="https://github.com/coqui-ai/TTS">Coqui TTS</a></b> (π₯34 Β· β 36K Β· π€) - - a deep learning toolkit for Text-to-Speech, battle-.. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/coqui-ai/TTS) (π¨βπ» 170 Β· π 4.4K Β· π₯ 3.8M Β· π¦ 2K Β· π 1.1K - 7% open Β· β±οΈ 10.02.2024):
```
git clone https://github.com/coqui-ai/TTS
```
- [PyPi](https://pypi.org/project/tts) (π₯ 150K / month Β· π¦ 53 Β· β±οΈ 12.12.2023):
```
pip install tts
```
- [Conda](https://anaconda.org/conda-forge/tts) (π₯ 20K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge tts
```
</details>
<details><summary><b><a href="https://github.com/magenta/magenta">Magenta</a></b> (π₯33 Β· β 19K) - Magenta: Music and Art Generation with Machine Intelligence. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/magenta/magenta) (π¨βπ» 160 Β· π 3.7K Β· π¦ 550 Β· π 1K - 41% open Β· β±οΈ 01.08.2024):
```
git clone https://github.com/magenta/magenta
```
- [PyPi](https://pypi.org/project/magenta) (π₯ 8.2K / month Β· π¦ 5 Β· β±οΈ 01.08.2022):
```
pip install magenta
```
</details>
<details><summary><b><a href="https://github.com/deezer/spleeter">spleeter</a></b> (π₯32 Β· β 26K) - Deezer source separation library including pretrained models. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/deezer/spleeter) (π¨βπ» 21 Β· π 2.9K Β· π₯ 3.6M Β· π¦ 850 Β· π 800 - 29% open Β· β±οΈ 29.10.2024):
```
git clone https://github.com/deezer/spleeter
```
- [PyPi](https://pypi.org/project/spleeter) (π₯ 27K / month Β· π¦ 12 Β· β±οΈ 10.06.2022):
```
pip install spleeter
```
- [Conda](https://anaconda.org/conda-forge/spleeter) (π₯ 99K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge spleeter
```
</details>
<details><summary><b><a href="https://github.com/librosa/librosa">librosa</a></b> (π₯31 Β· β 7.2K) - Python library for audio and music analysis. <code><a href="http://bit.ly/3hkKRql">ISC</a></code></summary>
- [GitHub](https://github.com/librosa/librosa) (π¨βπ» 120 Β· π 960 Β· π 1.2K - 4% open Β· β±οΈ 26.11.2024):
```
git clone https://github.com/librosa/librosa
```
- [PyPi](https://pypi.org/project/librosa) (π₯ 2.9M / month Β· π¦ 1.4K Β· β±οΈ 14.05.2024):
```
pip install librosa
```
- [Conda](https://anaconda.org/conda-forge/librosa) (π₯ 840K Β· β±οΈ 19.12.2024):
```
conda install -c conda-forge librosa
```
</details>
<details><summary><b><a href="https://github.com/iver56/audiomentations">audiomentations</a></b> (π₯31 Β· β 1.9K) - A Python library for audio data augmentation. Inspired by.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/iver56/audiomentations) (π¨βπ» 30 Β· π 190 Β· π¦ 630 Β· π 190 - 26% open Β· β±οΈ 09.12.2024):
```
git clone https://github.com/iver56/audiomentations
```
- [PyPi](https://pypi.org/project/audiomentations) (π₯ 48K / month Β· π¦ 21 Β· β±οΈ 06.12.2024):
```
pip install audiomentations
```
</details>
<details><summary><b><a href="https://github.com/Picovoice/porcupine">Porcupine</a></b> (π₯30 Β· β 3.8K) - On-device wake word detection powered by deep learning. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/Picovoice/porcupine) (π¨βπ» 39 Β· π 500 Β· π¦ 36 Β· π 560 - 0% open Β· β±οΈ 14.12.2024):
```
git clone https://github.com/Picovoice/Porcupine
```
- [PyPi](https://pypi.org/project/pvporcupine) (π₯ 11K / month Β· π¦ 35 Β· β±οΈ 27.08.2024):
```
pip install pvporcupine
```
</details>
<details><summary><b><a href="https://github.com/bastibe/python-soundfile">python-soundfile</a></b> (π₯30 Β· β 720) - SoundFile is an audio library based on libsndfile, CFFI, and.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/bastibe/python-soundfile) (π¨βπ» 37 Β· π 110 Β· π₯ 21K Β· π¦ 48K Β· π 260 - 47% open Β· β±οΈ 04.12.2024):
```
git clone https://github.com/bastibe/python-soundfile
```
- [PyPi](https://pypi.org/project/soundfile) (π₯ 3.7M / month Β· π¦ 780 Β· β±οΈ 15.02.2023):
```
pip install soundfile
```
- [Conda](https://anaconda.org/anaconda/pysoundfile):
```
conda install -c anaconda pysoundfile
```
</details>
<details><summary><b><a href="https://github.com/tinytag/tinytag">tinytag</a></b> (π₯30 Β· β 720) - Python library for reading audio file metadata. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/tinytag/tinytag) (π¨βπ» 27 Β· π 100 Β· π¦ 1.1K Β· π 120 - 3% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/devsnd/tinytag
```
- [PyPi](https://pypi.org/project/tinytag) (π₯ 64K / month Β· π¦ 110 Β· β±οΈ 03.11.2024):
```
pip install tinytag
```
</details>
<details><summary><b><a href="https://github.com/beetbox/audioread">audioread</a></b> (π₯29 Β· β 500 Β· π€) - cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/beetbox/audioread) (π¨βπ» 25 Β· π 110 Β· π¦ 27K Β· π 94 - 39% open Β· β±οΈ 15.12.2023):
```
git clone https://github.com/beetbox/audioread
```
- [PyPi](https://pypi.org/project/audioread) (π₯ 2.2M / month Β· π¦ 140 Β· β±οΈ 27.09.2023):
```
pip install audioread
```
- [Conda](https://anaconda.org/conda-forge/audioread) (π₯ 910K Β· β±οΈ 03.09.2024):
```
conda install -c conda-forge audioread
```
</details>
<details><summary><b><a href="https://github.com/CPJKU/madmom">Madmom</a></b> (π₯27 Β· β 1.4K) - Python audio and music signal processing library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/CPJKU/madmom) (π¨βπ» 24 Β· π 200 Β· π¦ 450 Β· π 280 - 24% open Β· β±οΈ 25.08.2024):
```
git clone https://github.com/CPJKU/madmom
```
- [PyPi](https://pypi.org/project/madmom) (π₯ 2.2K / month Β· π¦ 27 Β· β±οΈ 14.11.2018):
```
pip install madmom
```
</details>
<details><summary><b><a href="https://github.com/magenta/ddsp">DDSP</a></b> (π₯23 Β· β 2.9K) - DDSP: Differentiable Digital Signal Processing. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/magenta/ddsp) (π¨βπ» 32 Β· π 330 Β· π¦ 62 Β· π 170 - 28% open Β· β±οΈ 23.09.2024):
```
git clone https://github.com/magenta/ddsp
```
- [PyPi](https://pypi.org/project/ddsp) (π₯ 4.3K / month Β· π¦ 1 Β· β±οΈ 25.05.2022):
```
pip install ddsp
```
- [Conda](https://anaconda.org/conda-forge/ddsp) (π₯ 20K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge ddsp
```
</details>
<details><summary><b><a href="https://github.com/KinWaiCheuk/nnAudio">nnAudio</a></b> (π₯22 Β· β 1K Β· π€) - Audio processing by using pytorch 1D convolution network. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/KinWaiCheuk/nnAudio) (π¨βπ» 15 Β· π 90 Β· π¦ 250 Β· π 63 - 28% open Β· β±οΈ 13.02.2024):
```
git clone https://github.com/KinWaiCheuk/nnAudio
```
- [PyPi](https://pypi.org/project/nnAudio) (π₯ 21K / month Β· π¦ 4 Β· β±οΈ 13.02.2024):
```
pip install nnAudio
```
</details>
<details><summary>Show 13 hidden projects...</summary>
- <b><a href="https://github.com/jiaaro/pydub">Pydub</a></b> (π₯35 Β· β 9K Β· π) - Manipulate audio with a simple and easy high level interface. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/mozilla/DeepSpeech">DeepSpeech</a></b> (π₯33 Β· β 25K Β· π) - DeepSpeech is an open source embedded (offline, on-.. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/tyiannak/pyAudioAnalysis">pyAudioAnalysis</a></b> (π₯28 Β· β 5.9K Β· π) - Python Audio Analysis Library: Feature Extraction,.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/MTG/essentia">Essentia</a></b> (π₯28 Β· β 2.9K) - C++ library for audio and music analysis, description and.. <code><a href="http://bit.ly/3pwmjO5">βοΈAGPL-3.0</a></code>
- <b><a href="https://github.com/aubio/aubio">aubio</a></b> (π₯27 Β· β 3.3K Β· π€) - a library for audio and music analysis. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/mozilla/TTS">TTS</a></b> (π₯26 Β· β 9.5K Β· π) - Deep learning for Text to Speech (Discussion forum:.. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code>
- <b><a href="https://github.com/jameslyons/python_speech_features">python_speech_features</a></b> (π₯24 Β· β 2.4K Β· π) - This library provides common speech features for ASR.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/worldveil/dejavu">Dejavu</a></b> (π₯23 Β· β 6.5K Β· π) - Audio fingerprinting and recognition in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/keunwoochoi/kapre">kapre</a></b> (π₯22 Β· β 920 Β· π) - kapre: Keras Audio Preprocessors. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/Parisson/TimeSide">TimeSide</a></b> (π₯22 Β· β 370) - scalable audio processing framework and server written in Python. <code><a href="http://bit.ly/3pwmjO5">βοΈAGPL-3.0</a></code>
- <b><a href="https://github.com/adefossez/julius">Julius</a></b> (π₯21 Β· β 430 Β· π) - Fast PyTorch based DSP for audio and 1D signals. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/bmcfee/muda">Muda</a></b> (π₯18 Β· β 230 Β· π) - A library for augmenting annotated audio data. <code><a href="http://bit.ly/3hkKRql">ISC</a></code>
- <b><a href="https://github.com/facebookresearch/textlesslib">textlesslib</a></b> (π₯10 Β· β 530 Β· π) - Library for Textless Spoken Language Processing. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
</details>
<br>
## Geospatial Data
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries to load, process, analyze, and write geographic data as well as libraries for spatial analysis, map visualization, and geocoding._
<details><summary><b><a href="https://github.com/visgl/deck.gl">pydeck</a></b> (π₯43 Β· β 12K) - WebGL2 powered visualization framework. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/visgl/deck.gl) (π¨βπ» 280 Β· π 2.1K Β· π¦ 8.4K Β· π 3.1K - 11% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/visgl/deck.gl
```
- [PyPi](https://pypi.org/project/pydeck) (π₯ 6.7M / month Β· π¦ 120 Β· β±οΈ 10.05.2024):
```
pip install pydeck
```
- [Conda](https://anaconda.org/conda-forge/pydeck) (π₯ 660K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge pydeck
```
- [npm](https://www.npmjs.com/package/deck.gl) (π₯ 570K / month Β· π¦ 310 Β· β±οΈ 11.12.2024):
```
npm install deck.gl
```
</details>
<details><summary><b><a href="https://github.com/python-visualization/folium">folium</a></b> (π₯40 Β· β 7K Β· π) - Python Data. Leaflet.js Maps. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/python-visualization/folium) (π¨βπ» 170 Β· π 2.2K Β· π¦ 48K Β· π 1.1K - 7% open Β· β±οΈ 14.12.2024):
```
git clone https://github.com/python-visualization/folium
```
- [PyPi](https://pypi.org/project/folium) (π₯ 1.7M / month Β· π¦ 800 Β· β±οΈ 13.12.2024):
```
pip install folium
```
- [Conda](https://anaconda.org/conda-forge/folium) (π₯ 3.3M Β· β±οΈ 16.12.2024):
```
conda install -c conda-forge folium
```
</details>
<details><summary><b><a href="https://github.com/shapely/shapely">Shapely</a></b> (π₯40 Β· β 4K) - Manipulation and analysis of geometric objects. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/shapely/shapely) (π¨βπ» 160 Β· π 570 Β· π₯ 3.7K Β· π¦ 89K Β· π 1.3K - 23% open Β· β±οΈ 03.12.2024):
```
git clone https://github.com/shapely/shapely
```
- [PyPi](https://pypi.org/project/shapely) (π₯ 34M / month Β· π¦ 2.9K Β· β±οΈ 19.08.2024):
```
pip install shapely
```
- [Conda](https://anaconda.org/conda-forge/shapely) (π₯ 11M Β· β±οΈ 25.09.2024):
```
conda install -c conda-forge shapely
```
</details>
<details><summary><b><a href="https://github.com/geopandas/geopandas">GeoPandas</a></b> (π₯39 Β· β 4.6K) - Python tools for geographic data. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/geopandas/geopandas) (π¨βπ» 240 Β· π 930 Β· π₯ 2.9K Β· π¦ 46K Β· π 1.7K - 26% open Β· β±οΈ 13.12.2024):
```
git clone https://github.com/geopandas/geopandas
```
- [PyPi](https://pypi.org/project/geopandas) (π₯ 7.1M / month Β· π¦ 2.8K Β· β±οΈ 02.07.2024):
```
pip install geopandas
```
- [Conda](https://anaconda.org/conda-forge/geopandas) (π₯ 4.2M Β· β±οΈ 16.12.2024):
```
conda install -c conda-forge geopandas
```
</details>
<details><summary><b><a href="https://github.com/rasterio/rasterio">Rasterio</a></b> (π₯37 Β· β 2.3K) - Rasterio reads and writes geospatial raster datasets. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/rasterio/rasterio) (π¨βπ» 160 Β· π 540 Β· π₯ 980 Β· π¦ 14K Β· π 1.9K - 7% open Β· β±οΈ 15.12.2024):
```
git clone https://github.com/rasterio/rasterio
```
- [PyPi](https://pypi.org/project/rasterio) (π₯ 2.8M / month Β· π¦ 1.5K Β· β±οΈ 02.12.2024):
```
pip install rasterio
```
- [Conda](https://anaconda.org/conda-forge/rasterio) (π₯ 3.9M Β· β±οΈ 02.12.2024):
```
conda install -c conda-forge rasterio
```
</details>
<details><summary><b><a href="https://github.com/Esri/arcgis-python-api">ArcGIS API</a></b> (π₯36 Β· β 1.9K Β· π) - Documentation and samples for ArcGIS API for Python. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/Esri/arcgis-python-api) (π¨βπ» 94 Β· π 1.1K Β· π₯ 13K Β· π¦ 880 Β· π 790 - 10% open Β· β±οΈ 03.12.2024):
```
git clone https://github.com/Esri/arcgis-python-api
```
- [PyPi](https://pypi.org/project/arcgis) (π₯ 84K / month Β· π¦ 40 Β· β±οΈ 01.10.2024):
```
pip install arcgis
```
- [Docker Hub](https://hub.docker.com/r/esridocker/arcgis-api-python-notebook):
```
docker pull esridocker/arcgis-api-python-notebook
```
</details>
<details><summary><b><a href="https://github.com/Toblerity/Fiona">Fiona</a></b> (π₯36 Β· β 1.2K Β· π) - Fiona reads and writes geographic data files. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/Toblerity/Fiona) (π¨βπ» 76 Β· π 200 Β· π¦ 24K Β· π 810 - 3% open Β· β±οΈ 18.11.2024):
```
git clone https://github.com/Toblerity/Fiona
```
- [PyPi](https://pypi.org/project/fiona) (π₯ 4.7M / month Β· π¦ 300 Β· β±οΈ 16.09.2024):
```
pip install fiona
```
- [Conda](https://anaconda.org/conda-forge/fiona) (π₯ 6.3M Β· β±οΈ 06.12.2024):
```
conda install -c conda-forge fiona
```
</details>
<details><summary><b><a href="https://github.com/pyproj4/pyproj">pyproj</a></b> (π₯36 Β· β 1.1K) - Python interface to PROJ (cartographic projections and coordinate.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/pyproj4/pyproj) (π¨βπ» 69 Β· π 210 Β· π¦ 37K Β· π 630 - 5% open Β· β±οΈ 04.12.2024):
```
git clone https://github.com/pyproj4/pyproj
```
- [PyPi](https://pypi.org/project/pyproj) (π₯ 9.3M / month Β· π¦ 1.7K Β· β±οΈ 01.10.2024):
```
pip install pyproj
```
- [Conda](https://anaconda.org/conda-forge/pyproj) (π₯ 9.2M Β· β±οΈ 01.10.2024):
```
conda install -c conda-forge pyproj
```
</details>
<details><summary><b><a href="https://github.com/jupyter-widgets/ipyleaflet">ipyleaflet</a></b> (π₯33 Β· β 1.5K) - A Jupyter - Leaflet.js bridge. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/jupyter-widgets/ipyleaflet) (π¨βπ» 91 Β· π 360 Β· π¦ 13K Β· π 660 - 45% open Β· β±οΈ 05.12.2024):
```
git clone https://github.com/jupyter-widgets/ipyleaflet
```
- [PyPi](https://pypi.org/project/ipyleaflet) (π₯ 230K / month Β· π¦ 280 Β· β±οΈ 22.07.2024):
```
pip install ipyleaflet
```
- [Conda](https://anaconda.org/conda-forge/ipyleaflet) (π₯ 1.3M Β· β±οΈ 16.12.2024):
```
conda install -c conda-forge ipyleaflet
```
- [npm](https://www.npmjs.com/package/jupyter-leaflet) (π₯ 6.4K / month Β· π¦ 9 Β· β±οΈ 22.07.2024):
```
npm install jupyter-leaflet
```
</details>
<details><summary><b><a href="https://github.com/pysal/pysal">PySAL</a></b> (π₯30 Β· β 1.3K) - PySAL: Python Spatial Analysis Library Meta-Package. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/pysal/pysal) (π¨βπ» 79 Β· π 300 Β· π¦ 1.7K Β· π 650 - 2% open Β· β±οΈ 18.11.2024):
```
git clone https://github.com/pysal/pysal
```
- [PyPi](https://pypi.org/project/pysal) (π₯ 35K / month Β· π¦ 49 Β· β±οΈ 30.07.2024):
```
pip install pysal
```
- [Conda](https://anaconda.org/conda-forge/pysal) (π₯ 590K Β· β±οΈ 30.07.2024):
```
conda install -c conda-forge pysal
```
</details>
<details><summary><b><a href="https://github.com/jazzband/geojson">geojson</a></b> (π₯30 Β· β 930) - Python bindings and utilities for GeoJSON. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/jazzband/geojson) (π¨βπ» 58 Β· π 120 Β· π¦ 19K Β· π 100 - 24% open Β· β±οΈ 25.10.2024):
```
git clone https://github.com/jazzband/geojson
```
- [PyPi](https://pypi.org/project/geojson) (π₯ 2.9M / month Β· π¦ 700 Β· β±οΈ 05.11.2023):
```
pip install geojson
```
- [Conda](https://anaconda.org/conda-forge/geojson) (π₯ 890K Β· β±οΈ 16.12.2024):
```
conda install -c conda-forge geojson
```
</details>
<details><summary><b><a href="https://github.com/holoviz/geoviews">GeoViews</a></b> (π₯29 Β· β 600) - Simple, concise geographical visualization in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/holoviz/geoviews) (π¨βπ» 32 Β· π 77 Β· π¦ 1.2K Β· π 350 - 30% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/holoviz/geoviews
```
- [PyPi](https://pypi.org/project/geoviews) (π₯ 19K / month Β· π¦ 63 Β· β±οΈ 17.12.2024):
```
pip install geoviews
```
- [Conda](https://anaconda.org/conda-forge/geoviews) (π₯ 270K Β· β±οΈ 18.12.2024):
```
conda install -c conda-forge geoviews
```
</details>
<details><summary><b><a href="https://github.com/geospace-code/pymap3d">pymap3d</a></b> (π₯23 Β· β 400 Β· π€) - pure-Python (Numpy optional) 3D coordinate conversions for geospace.. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
- [GitHub](https://github.com/geospace-code/pymap3d) (π¨βπ» 18 Β· π 87 Β· π¦ 460 Β· π 58 - 15% open Β· β±οΈ 11.02.2024):
```
git clone https://github.com/geospace-code/pymap3d
```
- [PyPi](https://pypi.org/project/pymap3d) (π₯ 240K / month Β· π¦ 44 Β· β±οΈ 11.02.2024):
```
pip install pymap3d
```
- [Conda](https://anaconda.org/conda-forge/pymap3d) (π₯ 88K Β· β±οΈ 11.02.2024):
```
conda install -c conda-forge pymap3d
```
</details>
<details><summary>Show 9 hidden projects...</summary>
- <b><a href="https://github.com/geopy/geopy">geopy</a></b> (π₯33 Β· β 4.5K Β· π) - Geocoding library for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/DenisCarriere/geocoder">Geocoder</a></b> (π₯32 Β· β 1.6K Β· π) - Python Geocoder. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/pytroll/satpy">Satpy</a></b> (π₯32 Β· β 1.1K) - Python package for earth-observing satellite data processing. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/sentinelsat/sentinelsat">Sentinelsat</a></b> (π₯27 Β· β 990 Β· π€) - Search and download Copernicus Sentinel satellite images. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/earthlab/earthpy">EarthPy</a></b> (π₯26 Β· β 510 Β· π) - A package built to support working with spatial data using open.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/marceloprates/prettymaps">prettymaps</a></b> (π₯24 Β· β 11K) - A small set of Python functions to draw pretty maps from.. <code><a href="http://bit.ly/3pwmjO5">βοΈAGPL-3.0</a></code>
- <b><a href="https://github.com/mapbox/mapboxgl-jupyter">Mapbox GL</a></b> (π₯24 Β· β 670 Β· π) - Use Mapbox GL JS to visualize data in a Python Jupyter notebook. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/pbugnion/gmaps">gmaps</a></b> (π₯22 Β· β 760 Β· π) - Google maps for Jupyter notebooks. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/andrea-cuttone/geoplotlib">geoplotlib</a></b> (π₯20 Β· β 1K Β· π) - python toolbox for visualizing geographical data and making maps. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
</details>
<br>
## Financial Data
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for algorithmic stock/crypto trading, risk analytics, backtesting, technical analysis, and other tasks on financial data._
<details><summary><b><a href="https://github.com/ranaroussi/yfinance">yfinance</a></b> (π₯42 Β· β 15K) - Download market data from Yahoo! Finances API. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/ranaroussi/yfinance) (π¨βπ» 130 Β· π 2.4K Β· π¦ 55K Β· π 1.4K - 13% open Β· β±οΈ 08.12.2024):
```
git clone https://github.com/ranaroussi/yfinance
```
- [PyPi](https://pypi.org/project/yfinance) (π₯ 3.3M / month Β· π¦ 710 Β· β±οΈ 19.11.2024):
```
pip install yfinance
```
- [Conda](https://anaconda.org/ranaroussi/yfinance) (π₯ 97K Β· β±οΈ 16.06.2023):
```
conda install -c ranaroussi yfinance
```
</details>
<details><summary><b><a href="https://github.com/pmorissette/bt">bt</a></b> (π₯31 Β· β 2.3K) - bt - flexible backtesting for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/pmorissette/bt) (π¨βπ» 34 Β· π 430 Β· π¦ 1.6K Β· π 340 - 22% open Β· β±οΈ 01.12.2024):
```
git clone https://github.com/pmorissette/bt
```
- [PyPi](https://pypi.org/project/bt) (π₯ 8K / month Β· π¦ 10 Β· β±οΈ 06.08.2024):
```
pip install bt
```
- [Conda](https://anaconda.org/conda-forge/bt) (π₯ 55K Β· β±οΈ 21.09.2024):
```
conda install -c conda-forge bt
```
</details>
<details><summary><b><a href="https://github.com/microsoft/qlib">Qlib</a></b> (π₯29 Β· β 16K) - Qlib is an AI-oriented quantitative investment platform that aims to.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/microsoft/qlib) (π¨βπ» 130 Β· π 2.7K Β· π₯ 740 Β· π¦ 21 Β· π 940 - 26% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/microsoft/qlib
```
- [PyPi](https://pypi.org/project/pyqlib) (π₯ 4.8K / month Β· π¦ 1 Β· β±οΈ 24.05.2024):
```
pip install pyqlib
```
</details>
<details><summary><b><a href="https://github.com/pmorissette/ffn">ffn</a></b> (π₯29 Β· β 2.1K) - ffn - a financial function library for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/pmorissette/ffn) (π¨βπ» 35 Β· π 300 Β· π¦ 510 Β· π 130 - 17% open Β· β±οΈ 01.12.2024):
```
git clone https://github.com/pmorissette/ffn
```
- [PyPi](https://pypi.org/project/ffn) (π₯ 17K / month Β· π¦ 18 Β· β±οΈ 02.11.2024):
```
pip install ffn
```
- [Conda](https://anaconda.org/conda-forge/ffn) (π₯ 14K Β· β±οΈ 03.11.2024):
```
conda install -c conda-forge ffn
```
</details>
<details><summary><b><a href="https://github.com/RomelTorres/alpha_vantage">Alpha Vantage</a></b> (π₯27 Β· β 4.3K) - A python wrapper for Alpha Vantage API for financial data. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/RomelTorres/alpha_vantage) (π¨βπ» 44 Β· π 740 Β· π 290 - 0% open Β· β±οΈ 18.07.2024):
```
git clone https://github.com/RomelTorres/alpha_vantage
```
- [PyPi](https://pypi.org/project/alpha_vantage) (π₯ 42K / month Β· π¦ 35 Β· β±οΈ 18.07.2024):
```
pip install alpha_vantage
```
- [Conda](https://anaconda.org/conda-forge/alpha_vantage) (π₯ 8K Β· β±οΈ 09.08.2024):
```
conda install -c conda-forge alpha_vantage
```
</details>
<details><summary><b><a href="https://github.com/erdewit/ib_insync">IB-insync</a></b> (π₯27 Β· β 2.9K Β· π€) - Python sync/async framework for Interactive Brokers API. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
- [GitHub](https://github.com/erdewit/ib_insync) (π¨βπ» 36 Β· π 780 Β· π 590 - 3% open Β· β±οΈ 14.03.2024):
```
git clone https://github.com/erdewit/ib_insync
```
- [PyPi](https://pypi.org/project/ib_insync) (π₯ 36K / month Β· π¦ 44 Β· β±οΈ 21.11.2022):
```
pip install ib_insync
```
- [Conda](https://anaconda.org/conda-forge/ib-insync) (π₯ 51K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge ib-insync
```
</details>
<details><summary><b><a href="https://github.com/tensortrade-org/tensortrade">TensorTrade</a></b> (π₯26 Β· β 4.6K) - An open source reinforcement learning framework for training,.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/tensortrade-org/tensortrade) (π¨βπ» 61 Β· π 1K Β· π¦ 67 Β· π 260 - 20% open Β· β±οΈ 09.06.2024):
```
git clone https://github.com/tensortrade-org/tensortrade
```
- [PyPi](https://pypi.org/project/tensortrade) (π₯ 1.6K / month Β· π¦ 1 Β· β±οΈ 10.05.2021):
```
pip install tensortrade
```
- [Conda](https://anaconda.org/conda-forge/tensortrade) (π₯ 4.3K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge tensortrade
```
</details>
<details><summary><b><a href="https://github.com/jealous/stockstats">stockstats</a></b> (π₯25 Β· β 1.3K Β· π€) - Supply a wrapper ``StockDataFrame`` based on the.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/jealous/stockstats) (π¨βπ» 10 Β· π 300 Β· π¦ 1.1K Β· π 130 - 11% open Β· β±οΈ 05.01.2024):
```
git clone https://github.com/jealous/stockstats
```
- [PyPi](https://pypi.org/project/stockstats) (π₯ 11K / month Β· π¦ 11 Β· β±οΈ 30.07.2023):
```
pip install stockstats
```
</details>
<details><summary><b><a href="https://github.com/cuemacro/finmarketpy">finmarketpy</a></b> (π₯23 Β· β 3.5K) - Python library for backtesting trading strategies & analyzing.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/cuemacro/finmarketpy) (π¨βπ» 18 Β· π 490 Β· π₯ 57 Β· π¦ 16 Β· π 29 - 86% open Β· β±οΈ 09.11.2024):
```
git clone https://github.com/cuemacro/finmarketpy
```
- [PyPi](https://pypi.org/project/finmarketpy) (π₯ 520 / month Β· β±οΈ 19.05.2024):
```
pip install finmarketpy
```
</details>
<details><summary><b><a href="https://github.com/google/tf-quant-finance">tf-quant-finance</a></b> (π₯21 Β· β 4.6K) - High-performance TensorFlow library for quantitative.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/google/tf-quant-finance) (π¨βπ» 47 Β· π 580 Β· π 63 - 55% open Β· β±οΈ 06.11.2024):
```
git clone https://github.com/google/tf-quant-finance
```
- [PyPi](https://pypi.org/project/tf-quant-finance) (π₯ 720 / month Β· π¦ 3 Β· β±οΈ 19.08.2022):
```
pip install tf-quant-finance
```
</details>
<details><summary>Show 15 hidden projects...</summary>
- <b><a href="https://github.com/quantopian/zipline">zipline</a></b> (π₯32 Β· β 18K Β· π) - Zipline, a Pythonic Algorithmic Trading Library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/bashtage/arch">arch</a></b> (π₯32 Β· β 1.3K) - ARCH models in Python. <code>βUnlicensed</code>
- <b><a href="https://github.com/quantopian/pyfolio">pyfolio</a></b> (π₯31 Β· β 5.7K Β· π) - Portfolio and risk analytics in Python. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/bukosabino/ta">ta</a></b> (π₯30 Β· β 4.4K Β· π) - Technical Analysis Library using Pandas and Numpy. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/mementum/backtrader">backtrader</a></b> (π₯28 Β· β 15K Β· π) - Python Backtesting library for trading strategies. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/quantopian/alphalens">Alphalens</a></b> (π₯27 Β· β 3.4K Β· π) - Performance analysis of predictive (alpha) stock factors. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/quantopian/empyrical">empyrical</a></b> (π₯27 Β· β 1.3K Β· π) - Common financial risk and performance metrics. Used by.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/scrtlabs/catalyst">Enigma Catalyst</a></b> (π₯26 Β· β 2.5K Β· π) - An Algorithmic Trading Library for Crypto-Assets in.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/peerchemist/finta">FinTA</a></b> (π₯25 Β· β 2.1K Β· π) - Common financial technical indicators implemented in Pandas. <code><a href="http://bit.ly/37RvQcA">βοΈLGPL-3.0</a></code>
- <b><a href="https://github.com/gbeced/pyalgotrade">PyAlgoTrade</a></b> (π₯24 Β· β 4.5K Β· π) - Python Algorithmic Trading Library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/kernc/backtesting.py">Backtesting.py</a></b> (π₯22 Β· β 5.7K Β· π) - Backtest trading strategies in Python. <code><a href="http://bit.ly/3pwmjO5">βοΈAGPL-3.0</a></code>
- <b><a href="https://github.com/CryptoSignal/Crypto-Signal">Crypto Signals</a></b> (π₯22 Β· β 5K Β· π) - Github.com/CryptoSignal - Trading & Technical Analysis Bot -.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/fmilthaler/FinQuant">FinQuant</a></b> (π₯22 Β· β 1.5K Β· π) - A program for financial portfolio management, analysis and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/tradytics/surpriver">surpriver</a></b> (π₯12 Β· β 1.8K Β· π) - Find big moving stocks before they move using machine.. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/alvarobartt/pyrtfolio">pyrtfolio</a></b> (π₯9 Β· β 150 Β· π) - Python package to generate stock portfolios. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
</details>
<br>
## Time Series Data
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for forecasting, anomaly detection, feature extraction, and machine learning on time-series and sequential data._
<details><summary><b><a href="https://github.com/sktime/sktime">sktime</a></b> (π₯39 Β· β 8K Β· π) - A unified framework for machine learning with time series. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/sktime/sktime) (π¨βπ» 430 Β· π 1.4K Β· π₯ 110 Β· π¦ 3.7K Β· π 2.6K - 37% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/alan-turing-institute/sktime
```
- [PyPi](https://pypi.org/project/sktime) (π₯ 970K / month Β· π¦ 130 Β· β±οΈ 09.12.2024):
```
pip install sktime
```
- [Conda](https://anaconda.org/conda-forge/sktime-all-extras) (π₯ 1M Β· β±οΈ 14.12.2024):
```
conda install -c conda-forge sktime-all-extras
```
</details>
<details><summary><b><a href="https://github.com/facebook/prophet">Prophet</a></b> (π₯35 Β· β 19K) - Tool for producing high quality forecasts for time series data that has.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/facebook/prophet) (π¨βπ» 180 Β· π 4.5K Β· π₯ 2.9K Β· π¦ 21 Β· π 2.2K - 19% open Β· β±οΈ 20.10.2024):
```
git clone https://github.com/facebook/prophet
```
- [PyPi](https://pypi.org/project/fbprophet) (π₯ 220K / month Β· π¦ 91 Β· β±οΈ 05.09.2020):
```
pip install fbprophet
```
- [Conda](https://anaconda.org/conda-forge/prophet) (π₯ 1.3M Β· β±οΈ 04.10.2024):
```
conda install -c conda-forge prophet
```
</details>
<details><summary><b><a href="https://github.com/Nixtla/statsforecast">StatsForecast</a></b> (π₯34 Β· β 4K) - Lightning fast forecasting with statistical and econometric.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/Nixtla/statsforecast) (π¨βπ» 48 Β· π 290 Β· π¦ 1.3K Β· π 350 - 29% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/Nixtla/statsforecast
```
- [PyPi](https://pypi.org/project/statsforecast) (π₯ 1.1M / month Β· π¦ 59 Β· β±οΈ 26.11.2024):
```
pip install statsforecast
```
- [Conda](https://anaconda.org/conda-forge/statsforecast) (π₯ 120K Β· β±οΈ 05.12.2024):
```
conda install -c conda-forge statsforecast
```
</details>
<details><summary><b><a href="https://github.com/blue-yonder/tsfresh">tsfresh</a></b> (π₯32 Β· β 8.5K) - Automatic extraction of relevant features from time series:. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/blue-yonder/tsfresh) (π¨βπ» 98 Β· π 1.2K Β· π¦ 21 Β· π 540 - 12% open Β· β±οΈ 19.11.2024):
```
git clone https://github.com/blue-yonder/tsfresh
```
- [PyPi](https://pypi.org/project/tsfresh) (π₯ 250K / month Β· π¦ 93 Β· β±οΈ 03.08.2024):
```
pip install tsfresh
```
- [Conda](https://anaconda.org/conda-forge/tsfresh) (π₯ 1.4M Β· β±οΈ 04.08.2024):
```
conda install -c conda-forge tsfresh
```
</details>
<details><summary><b><a href="https://github.com/unit8co/darts">Darts</a></b> (π₯32 Β· β 8.2K) - A python library for user-friendly forecasting and anomaly detection.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/unit8co/darts) (π¨βπ» 120 Β· π 880 Β· π 1.6K - 15% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/unit8co/darts
```
- [PyPi](https://pypi.org/project/u8darts) (π₯ 82K / month Β· π¦ 10 Β· β±οΈ 13.10.2024):
```
pip install u8darts
```
- [Conda](https://anaconda.org/conda-forge/u8darts-all) (π₯ 65K Β· β±οΈ 13.10.2024):
```
conda install -c conda-forge u8darts-all
```
- [Docker Hub](https://hub.docker.com/r/unit8/darts) (π₯ 930 Β· β±οΈ 17.04.2024):
```
docker pull unit8/darts
```
</details>
<details><summary><b><a href="https://github.com/sktime/pytorch-forecasting">pytorch-forecasting</a></b> (π₯32 Β· β 4K) - Time series forecasting with PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/sktime/pytorch-forecasting) (π¨βπ» 59 Β· π 630 Β· π¦ 460 Β· π 800 - 61% open Β· β±οΈ 10.12.2024):
```
git clone https://github.com/jdb78/pytorch-forecasting
```
- [PyPi](https://pypi.org/project/pytorch-forecasting) (π₯ 63K / month Β· π¦ 22 Β· β±οΈ 19.11.2024):
```
pip install pytorch-forecasting
```
- [Conda](https://anaconda.org/conda-forge/pytorch-forecasting) (π₯ 69K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge pytorch-forecasting
```
</details>
<details><summary><b><a href="https://github.com/TDAmeritrade/stumpy">STUMPY</a></b> (π₯32 Β· β 3.7K) - STUMPY is a powerful and scalable Python library for modern time series.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/TDAmeritrade/stumpy) (π¨βπ» 41 Β· π 320 Β· π¦ 980 Β· π 520 - 13% open Β· β±οΈ 17.11.2024):
```
git clone https://github.com/TDAmeritrade/stumpy
```
- [PyPi](https://pypi.org/project/stumpy) (π₯ 290K / month Β· π¦ 30 Β· β±οΈ 09.07.2024):
```
pip install stumpy
```
- [Conda](https://anaconda.org/conda-forge/stumpy) (π₯ 1M Β· β±οΈ 09.07.2024):
```
conda install -c conda-forge stumpy
```
</details>
<details><summary><b><a href="https://github.com/Nixtla/neuralforecast">NeuralForecast</a></b> (π₯32 Β· β 3.2K) - Scalable and user friendly neural forecasting algorithms. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/Nixtla/neuralforecast) (π¨βπ» 48 Β· π 370 Β· π¦ 270 Β· π 580 - 20% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/Nixtla/neuralforecast
```
- [PyPi](https://pypi.org/project/neuralforecast) (π₯ 64K / month Β· π¦ 21 Β· β±οΈ 16.12.2024):
```
pip install neuralforecast
```
- [Conda](https://anaconda.org/conda-forge/neuralforecast) (π₯ 27K Β· β±οΈ 17.12.2024):
```
conda install -c conda-forge neuralforecast
```
</details>
<details><summary><b><a href="https://github.com/alkaline-ml/pmdarima">pmdarima</a></b> (π₯32 Β· β 1.6K) - A statistical library designed to fill the void in Pythons time series.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/alkaline-ml/pmdarima) (π¨βπ» 23 Β· π 230 Β· π¦ 10K Β· π 340 - 19% open Β· β±οΈ 07.11.2024):
```
git clone https://github.com/alkaline-ml/pmdarima
```
- [PyPi](https://pypi.org/project/pmdarima) (π₯ 2.5M / month Β· π¦ 150 Β· β±οΈ 23.10.2023):
```
pip install pmdarima
```
- [Conda](https://anaconda.org/conda-forge/pmdarima) (π₯ 1.2M Β· β±οΈ 14.07.2024):
```
conda install -c conda-forge pmdarima
```
</details>
<details><summary><b><a href="https://github.com/skforecast/skforecast">skforecast</a></b> (π₯31 Β· β 1.2K) - Time series forecasting with machine learning models. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/skforecast/skforecast) (π¨βπ» 17 Β· π 140 Β· π¦ 380 Β· π 180 - 11% open Β· β±οΈ 28.11.2024):
```
git clone https://github.com/JoaquinAmatRodrigo/skforecast
```
- [PyPi](https://pypi.org/project/skforecast) (π₯ 95K / month Β· π¦ 15 Β· β±οΈ 11.11.2024):
```
pip install skforecast
```
</details>
<details><summary><b><a href="https://github.com/awslabs/gluonts">GluonTS</a></b> (π₯30 Β· β 4.7K) - Probabilistic time series modeling in Python. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/awslabs/gluonts) (π¨βπ» 120 Β· π 760 Β· π 960 - 33% open Β· β±οΈ 05.11.2024):
```
git clone https://github.com/awslabs/gluon-ts
```
- [PyPi](https://pypi.org/project/gluonts) (π₯ 790K / month Β· π¦ 33 Β· β±οΈ 11.11.2024):
```
pip install gluonts
```
- [Conda](https://anaconda.org/anaconda/gluonts) (π₯ 1.2K Β· β±οΈ 16.12.2024):
```
conda install -c anaconda gluonts
```
</details>
<details><summary><b><a href="https://github.com/tslearn-team/tslearn">tslearn</a></b> (π₯30 Β· β 2.9K) - The machine learning toolkit for time series analysis in Python. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tslearn-team/tslearn) (π¨βπ» 43 Β· π 340 Β· π¦ 1.5K Β· π 340 - 41% open Β· β±οΈ 01.07.2024):
```
git clone https://github.com/tslearn-team/tslearn
```
- [PyPi](https://pypi.org/project/tslearn) (π₯ 400K / month Β· π¦ 79 Β· β±οΈ 12.12.2023):
```
pip install tslearn
```
- [Conda](https://anaconda.org/conda-forge/tslearn) (π₯ 1.5M Β· β±οΈ 26.07.2024):
```
conda install -c conda-forge tslearn
```
</details>
<details><summary><b><a href="https://github.com/ourownstory/neural_prophet">NeuralProphet</a></b> (π₯27 Β· β 3.9K) - NeuralProphet: A simple forecasting package. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/ourownstory/neural_prophet) (π¨βπ» 56 Β· π 480 Β· π 560 - 10% open Β· β±οΈ 13.09.2024):
```
git clone https://github.com/ourownstory/neural_prophet
```
- [PyPi](https://pypi.org/project/neuralprophet) (π₯ 76K / month Β· π¦ 8 Β· β±οΈ 26.06.2024):
```
pip install neuralprophet
```
</details>
<details><summary><b><a href="https://github.com/python-streamz/streamz">Streamz</a></b> (π₯26 Β· β 1.2K) - Real-time stream processing for python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/python-streamz/streamz) (π¨βπ» 49 Β· π 150 Β· π¦ 510 Β· π 270 - 44% open Β· β±οΈ 22.11.2024):
```
git clone https://github.com/python-streamz/streamz
```
- [PyPi](https://pypi.org/project/streamz) (π₯ 22K / month Β· π¦ 57 Β· β±οΈ 27.07.2022):
```
pip install streamz
```
- [Conda](https://anaconda.org/conda-forge/streamz) (π₯ 1.3M Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge streamz
```
</details>
<details><summary><b><a href="https://github.com/fraunhoferportugal/tsfel">TSFEL</a></b> (π₯23 Β· β 950) - An intuitive library to extract features from time series. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/fraunhoferportugal/tsfel) (π¨βπ» 20 Β· π 140 Β· π¦ 160 Β· π 79 - 8% open Β· β±οΈ 17.10.2024):
```
git clone https://github.com/fraunhoferportugal/tsfel
```
- [PyPi](https://pypi.org/project/tsfel) (π₯ 14K / month Β· π¦ 7 Β· β±οΈ 12.09.2024):
```
pip install tsfel
```
</details>
<details><summary><b><a href="https://github.com/linkedin/greykite">greykite</a></b> (π₯21 Β· β 1.8K Β· π€) - A flexible, intuitive and fast forecasting library. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
- [GitHub](https://github.com/linkedin/greykite) (π¨βπ» 10 Β· π 110 Β· π₯ 36 Β· π¦ 36 Β· π 110 - 27% open Β· β±οΈ 16.01.2024):
```
git clone https://github.com/linkedin/greykite
```
- [PyPi](https://pypi.org/project/greykite) (π₯ 8.7K / month Β· β±οΈ 12.01.2024):
```
pip install greykite
```
</details>
<details><summary><b><a href="https://github.com/wwrechard/pydlm">pydlm</a></b> (π₯20 Β· β 480) - A python library for Bayesian time series modeling. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/wwrechard/pydlm) (π¨βπ» 7 Β· π 98 Β· π¦ 37 Β· π 56 - 73% open Β· β±οΈ 07.09.2024):
```
git clone https://github.com/wwrechard/pydlm
```
- [PyPi](https://pypi.org/project/pydlm) (π₯ 37K / month Β· π¦ 2 Β· β±οΈ 13.08.2024):
```
pip install pydlm
```
</details>
<details><summary><b><a href="https://github.com/predict-idlab/tsflex">tsflex</a></b> (π₯20 Β· β 410) - Flexible time series feature extraction & processing. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/predict-idlab/tsflex) (π¨βπ» 6 Β· π 26 Β· π¦ 17 Β· π 56 - 58% open Β· β±οΈ 06.09.2024):
```
git clone https://github.com/predict-idlab/tsflex
```
- [PyPi](https://pypi.org/project/tsflex) (π₯ 1.1K / month Β· π¦ 2 Β· β±οΈ 06.09.2024):
```
pip install tsflex
```
- [Conda](https://anaconda.org/conda-forge/tsflex) (π₯ 28K Β· β±οΈ 08.04.2024):
```
conda install -c conda-forge tsflex
```
</details>
<details><summary><b><a href="https://github.com/AutoViML/Auto_TS">Auto TS</a></b> (π₯19 Β· β 740 Β· π€) - Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/AutoViML/Auto_TS) (π¨βπ» 13 Β· π 120 Β· π 90 - 3% open Β· β±οΈ 05.05.2024):
```
git clone https://github.com/AutoViML/Auto_TS
```
- [PyPi](https://pypi.org/project/auto-ts) (π₯ 11K / month Β· β±οΈ 05.05.2024):
```
pip install auto-ts
```
</details>
<details><summary>Show 10 hidden projects...</summary>
- <b><a href="https://github.com/johannfaouzi/pyts">pyts</a></b> (π₯26 Β· β 1.8K Β· π) - A Python package for time series classification. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/RJT1990/pyflux">PyFlux</a></b> (π₯25 Β· β 2.1K Β· π) - Open source time series library for Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/linkedin/luminol">luminol</a></b> (π₯22 Β· β 1.2K Β· π) - Anomaly Detection and Correlation library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/X-DataInitiative/tick">tick</a></b> (π₯22 Β· β 500 Β· π) - Module for statistical learning, with a particular emphasis on time-.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/arundo/adtk">ADTK</a></b> (π₯21 Β· β 1.1K Β· π) - A Python toolkit for rule-based/unsupervised anomaly detection in.. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code>
- <b><a href="https://github.com/dmbee/seglearn">seglearn</a></b> (π₯21 Β· β 570 Β· π) - Python module for machine learning time series:. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/target/matrixprofile-ts">matrixprofile-ts</a></b> (π₯19 Β· β 730 Β· π) - A Python library for detecting patterns and anomalies.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/firmai/atspy">atspy</a></b> (π₯15 Β· β 510 Β· π) - AtsPy: Automated Time Series Models in Python (by @firmai). <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/arundo/tsaug">tsaug</a></b> (π₯14 Β· β 350 Β· π) - A Python package for time series augmentation. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/hsbc/tslumen">tslumen</a></b> (π₯8 Β· β 68 Β· π) - A library for Time Series EDA (exploratory data analysis). <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
</details>
<br>
## Medical Data
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for processing and analyzing medical data such as MRIs, EEGs, genomic data, and other medical imaging formats._
<details><summary><b><a href="https://github.com/mne-tools/mne-python">MNE</a></b> (π₯39 Β· β 2.8K) - MNE: Magnetoencephalography (MEG) and Electroencephalography (EEG) in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/mne-tools/mne-python) (π¨βπ» 380 Β· π 1.3K Β· π¦ 4.8K Β· π 5K - 11% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/mne-tools/mne-python
```
- [PyPi](https://pypi.org/project/mne) (π₯ 150K / month Β· π¦ 420 Β· β±οΈ 18.12.2024):
```
pip install mne
```
- [Conda](https://anaconda.org/conda-forge/mne) (π₯ 460K Β· β±οΈ 19.12.2024):
```
conda install -c conda-forge mne
```
</details>
<details><summary><b><a href="https://github.com/nilearn/nilearn">Nilearn</a></b> (π₯39 Β· β 1.2K) - Machine learning for NeuroImaging in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/nilearn/nilearn) (π¨βπ» 250 Β· π 600 Β· π₯ 270 Β· π¦ 3.6K Β· π 2.2K - 13% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/nilearn/nilearn
```
- [PyPi](https://pypi.org/project/nilearn) (π₯ 70K / month Β· π¦ 310 Β· β±οΈ 02.12.2024):
```
pip install nilearn
```
- [Conda](https://anaconda.org/conda-forge/nilearn) (π₯ 310K Β· β±οΈ 02.12.2024):
```
conda install -c conda-forge nilearn
```
</details>
<details><summary><b><a href="https://github.com/Project-MONAI/MONAI">MONAI</a></b> (π₯36 Β· β 6K) - AI Toolkit for Healthcare Imaging. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/Project-MONAI/MONAI) (π¨βπ» 210 Β· π 1.1K Β· π¦ 3.3K Β· π 3.2K - 12% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/Project-MONAI/MONAI
```
- [PyPi](https://pypi.org/project/monai) (π₯ 240K / month Β· π¦ 140 Β· β±οΈ 10.12.2024):
```
pip install monai
```
- [Conda](https://anaconda.org/conda-forge/monai) (π₯ 36K Β· β±οΈ 17.10.2024):
```
conda install -c conda-forge monai
```
</details>
<details><summary><b><a href="https://github.com/nipy/nipype">NIPYPE</a></b> (π₯36 Β· β 750) - Workflows and interfaces for neuroimaging packages. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/nipy/nipype) (π¨βπ» 260 Β· π 530 Β· π¦ 5.4K Β· π 1.4K - 30% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/nipy/nipype
```
- [PyPi](https://pypi.org/project/nipype) (π₯ 230K / month Β· π¦ 150 Β· β±οΈ 17.12.2024):
```
pip install nipype
```
- [Conda](https://anaconda.org/conda-forge/nipype) (π₯ 730K Β· β±οΈ 18.12.2024):
```
conda install -c conda-forge nipype
```
</details>
<details><summary><b><a href="https://github.com/nipy/nibabel">NiBabel</a></b> (π₯36 Β· β 660) - Python package to access a cacophony of neuro-imaging file formats. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/nipy/nibabel) (π¨βπ» 110 Β· π 260 Β· π¦ 24K Β· π 540 - 23% open Β· β±οΈ 07.12.2024):
```
git clone https://github.com/nipy/nibabel
```
- [PyPi](https://pypi.org/project/nibabel) (π₯ 1.6M / month Β· π¦ 1.2K Β· β±οΈ 23.10.2024):
```
pip install nibabel
```
- [Conda](https://anaconda.org/conda-forge/nibabel) (π₯ 810K Β· β±οΈ 12.12.2024):
```
conda install -c conda-forge nibabel
```
</details>
<details><summary><b><a href="https://github.com/CamDavidsonPilon/lifelines">Lifelines</a></b> (π₯33 Β· β 2.4K) - Survival analysis in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/CamDavidsonPilon/lifelines) (π¨βπ» 120 Β· π 560 Β· π¦ 3.2K Β· π 980 - 27% open Β· β±οΈ 29.10.2024):
```
git clone https://github.com/CamDavidsonPilon/lifelines
```
- [PyPi](https://pypi.org/project/lifelines) (π₯ 2.5M / month Β· π¦ 160 Β· β±οΈ 29.10.2024):
```
pip install lifelines
```
- [Conda](https://anaconda.org/conda-forge/lifelines) (π₯ 390K Β· β±οΈ 19.12.2024):
```
conda install -c conda-forge lifelines
```
</details>
<details><summary><b><a href="https://github.com/hail-is/hail">Hail</a></b> (π₯33 Β· β 980) - Cloud-native genomic dataframes and batch computing. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/hail-is/hail) (π¨βπ» 97 Β· π 250 Β· π¦ 150 Β· π 2.5K - 10% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/hail-is/hail
```
- [PyPi](https://pypi.org/project/hail) (π₯ 270K / month Β· π¦ 34 Β· β±οΈ 04.10.2024):
```
pip install hail
```
</details>
<details><summary><b><a href="https://github.com/google/deepvariant">DeepVariant</a></b> (π₯27 Β· β 3.3K) - DeepVariant is an analysis pipeline that uses a deep neural.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/google/deepvariant) (π¨βπ» 36 Β· π 720 Β· π₯ 4.8K Β· π 850 - 0% open Β· β±οΈ 09.12.2024):
```
git clone https://github.com/google/deepvariant
```
- [Conda](https://anaconda.org/bioconda/deepvariant) (π₯ 72K Β· β±οΈ 16.06.2023):
```
conda install -c bioconda deepvariant
```
</details>
<details><summary><b><a href="https://github.com/brainiak/brainiak">Brainiak</a></b> (π₯20 Β· β 340) - Brain Imaging Analysis Kit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/brainiak/brainiak) (π¨βπ» 35 Β· π 140 Β· π 230 - 39% open Β· β±οΈ 09.12.2024):
```
git clone https://github.com/brainiak/brainiak
```
- [PyPi](https://pypi.org/project/brainiak) (π₯ 3.7K / month Β· β±οΈ 11.12.2024):
```
pip install brainiak
```
- [Docker Hub](https://hub.docker.com/r/brainiak/brainiak) (π₯ 1.9K Β· β 1 Β· β±οΈ 15.10.2020):
```
docker pull brainiak/brainiak
```
</details>
<details><summary>Show 10 hidden projects...</summary>
- <b><a href="https://github.com/dipy/dipy">DIPY</a></b> (π₯32 Β· β 720) - DIPY is the paragon 3D/4D+ medical imaging library in Python... <code>βUnlicensed</code>
- <b><a href="https://github.com/nipy/nipy">NIPY</a></b> (π₯27 Β· β 380) - Neuroimaging in Python FMRI analysis package. <code>βUnlicensed</code>
- <b><a href="https://github.com/NifTK/NiftyNet">NiftyNet</a></b> (π₯25 Β· β 1.4K Β· π) - [unmaintained] An open-source convolutional neural.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/loli/medpy">MedPy</a></b> (π₯24 Β· β 580) - Medical image processing in Python. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/projectglow/glow">Glow</a></b> (π₯21 Β· β 270) - An open-source toolkit for large-scale genomic analysis. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/DLTK/DLTK">DLTK</a></b> (π₯20 Β· β 1.4K Β· π) - Deep Learning Toolkit for Medical Image Analysis. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/perone/medicaltorch">MedicalTorch</a></b> (π₯15 Β· β 860 Β· π) - A medical imaging framework for Pytorch. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/MIC-DKFZ/medicaldetectiontoolkit">Medical Detection Toolkit</a></b> (π₯14 Β· β 1.3K Β· π) - The Medical Detection Toolkit contains 2D + 3D.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/QTIM-Lab/DeepNeuro">DeepNeuro</a></b> (π₯14 Β· β 120 Β· π) - A deep learning python package for neuroimaging data. Made by:. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/Tencent/MedicalNet">MedicalNet</a></b> (π₯12 Β· β 2K Β· π) - Many studies have shown that the performance on deep learning is.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
</details>
<br>
## Tabular Data
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for processing tabular and structured data._
<details><summary><b><a href="https://github.com/manujosephv/pytorch_tabular">pytorch_tabular</a></b> (π₯25 Β· β 1.4K) - A standard framework for modelling Deep Learning Models.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/manujosephv/pytorch_tabular) (π¨βπ» 25 Β· π 140 Β· π₯ 52 Β· π 160 - 6% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/manujosephv/pytorch_tabular
```
- [PyPi](https://pypi.org/project/pytorch_tabular) (π₯ 5.5K / month Β· π¦ 9 Β· β±οΈ 28.11.2024):
```
pip install pytorch_tabular
```
</details>
<details><summary><b><a href="https://github.com/AnotherSamWilson/miceforest">miceforest</a></b> (π₯23 Β· β 360) - Multiple Imputation with LightGBM in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/AnotherSamWilson/miceforest) (π¨βπ» 8 Β· π 30 Β· π¦ 180 Β· π 85 - 8% open Β· β±οΈ 02.08.2024):
```
git clone https://github.com/AnotherSamWilson/miceforest
```
- [PyPi](https://pypi.org/project/miceforest) (π₯ 61K / month Β· π¦ 9 Β· β±οΈ 02.08.2024):
```
pip install miceforest
```
- [Conda](https://anaconda.org/conda-forge/miceforest) (π₯ 16K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge miceforest
```
</details>
<details><summary><b><a href="https://github.com/upgini/upgini">upgini</a></b> (π₯21 Β· β 320) - Data search & enrichment library for Machine Learning Easily find and add.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/upgini/upgini) (π¨βπ» 13 Β· π 25 Β· π¦ 9 Β· β±οΈ 18.12.2024):
```
git clone https://github.com/upgini/upgini
```
- [PyPi](https://pypi.org/project/upgini) (π₯ 16K / month Β· β±οΈ 19.12.2024):
```
pip install upgini
```
</details>
<details><summary><b><a href="https://github.com/carefree0910/carefree-learn">carefree-learn</a></b> (π₯18 Β· β 410 Β· π€) - Deep Learning PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/carefree0910/carefree-learn) (π¨βπ» 1 Β· π 38 Β· π¦ 8 Β· π 82 - 2% open Β· β±οΈ 18.03.2024):
```
git clone https://github.com/carefree0910/carefree-learn
```
- [PyPi](https://pypi.org/project/carefree-learn) (π₯ 1.7K / month Β· β±οΈ 09.01.2024):
```
pip install carefree-learn
```
</details>
<details><summary>Show 1 hidden projects...</summary>
- <b><a href="https://github.com/firmai/deltapy">deltapy</a></b> (π₯13 Β· β 540 Β· π) - DeltaPy - Tabular Data Augmentation (by @firmai). <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
</details>
<br>
## Optical Character Recognition
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for optical character recognition (OCR) and text extraction from images or videos._
<details><summary><b><a href="https://github.com/PaddlePaddle/PaddleOCR">PaddleOCR</a></b> (π₯41 Β· β 45K) - Awesome multilingual OCR toolkits based on PaddlePaddle.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/PaddlePaddle/PaddleOCR) (π¨βπ» 270 Β· π 7.8K Β· π₯ 900K Β· π¦ 3.9K Β· π 9.5K - 1% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/PaddlePaddle/PaddleOCR
```
- [PyPi](https://pypi.org/project/paddleocr) (π₯ 380K / month Β· π¦ 110 Β· β±οΈ 22.10.2024):
```
pip install paddleocr
```
</details>
<details><summary><b><a href="https://github.com/ocrmypdf/OCRmyPDF">OCRmyPDF</a></b> (π₯35 Β· β 14K) - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing them.. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code></summary>
- [GitHub](https://github.com/ocrmypdf/OCRmyPDF) (π¨βπ» 100 Β· π 1K Β· π₯ 6K Β· π¦ 1.1K Β· π 1.2K - 9% open Β· β±οΈ 13.12.2024):
```
git clone https://github.com/ocrmypdf/OCRmyPDF
```
- [PyPi](https://pypi.org/project/ocrmypdf) (π₯ 190K / month Β· π¦ 37 Β· β±οΈ 09.12.2024):
```
pip install ocrmypdf
```
- [Conda](https://anaconda.org/conda-forge/ocrmypdf) (π₯ 85K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge ocrmypdf
```
</details>
<details><summary><b><a href="https://github.com/JaidedAI/EasyOCR">EasyOCR</a></b> (π₯34 Β· β 25K) - Ready-to-use OCR with 80+ supported languages and all popular writing.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/JaidedAI/EasyOCR) (π¨βπ» 130 Β· π 3.2K Β· π₯ 17M Β· π¦ 10K Β· π 1K - 42% open Β· β±οΈ 24.09.2024):
```
git clone https://github.com/JaidedAI/EasyOCR
```
- [PyPi](https://pypi.org/project/easyocr) (π₯ 760K / month Β· π¦ 210 Β· β±οΈ 24.09.2024):
```
pip install easyocr
```
</details>
<details><summary><b><a href="https://github.com/madmaze/pytesseract">Tesseract</a></b> (π₯33 Β· β 5.9K) - Python-tesseract is an optical character recognition (OCR) tool.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/madmaze/pytesseract) (π¨βπ» 49 Β· π 720 Β· π 360 - 2% open Β· β±οΈ 22.11.2024):
```
git clone https://github.com/madmaze/pytesseract
```
- [PyPi](https://pypi.org/project/pytesseract) (π₯ 2.6M / month Β· π¦ 970 Β· β±οΈ 16.08.2024):
```
pip install pytesseract
```
- [Conda](https://anaconda.org/conda-forge/pytesseract) (π₯ 640K Β· β±οΈ 15.10.2023):
```
conda install -c conda-forge pytesseract
```
</details>
<details><summary><b><a href="https://github.com/sirfz/tesserocr">tesserocr</a></b> (π₯30 Β· β 2K) - A Python wrapper for the tesseract-ocr API. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/sirfz/tesserocr) (π¨βπ» 30 Β· π 250 Β· π₯ 700 Β· π¦ 1.1K Β· π 280 - 18% open Β· β±οΈ 25.11.2024):
```
git clone https://github.com/sirfz/tesserocr
```
- [PyPi](https://pypi.org/project/tesserocr) (π₯ 82K / month Β· π¦ 36 Β· β±οΈ 26.08.2024):
```
pip install tesserocr
```
- [Conda](https://anaconda.org/conda-forge/tesserocr) (π₯ 210K Β· β±οΈ 13.09.2024):
```
conda install -c conda-forge tesserocr
```
</details>
<details><summary><b><a href="https://github.com/open-mmlab/mmocr">MMOCR</a></b> (π₯26 Β· β 4.4K) - OpenMMLab Text Detection, Recognition and Understanding Toolbox. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/open-mmlab/mmocr) (π¨βπ» 90 Β· π 750 Β· π¦ 180 Β· π 930 - 20% open Β· β±οΈ 27.11.2024):
```
git clone https://github.com/open-mmlab/mmocr
```
- [PyPi](https://pypi.org/project/mmocr) (π₯ 4.4K / month Β· π¦ 4 Β· β±οΈ 05.05.2022):
```
pip install mmocr
```
</details>
<details><summary>Show 6 hidden projects...</summary>
- <b><a href="https://github.com/faustomorales/keras-ocr">keras-ocr</a></b> (π₯25 Β· β 1.4K Β· π) - A packaged and flexible version of the CRAFT text detector.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/Calamari-OCR/calamari">calamari</a></b> (π₯24 Β· β 1.1K) - Line based ATR Engine based on OCRopy. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/WZBSocialScienceCenter/pdftabextract">pdftabextract</a></b> (π₯21 Β· β 2.2K Β· π) - A set of tools for extracting tables from PDF files.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/emedvedev/attention-ocr">attention-ocr</a></b> (π₯21 Β· β 1.1K Β· π) - A Tensorflow model for text recognition (CNN + seq2seq.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/jlsutherland/doc2text">doc2text</a></b> (π₯20 Β· β 1.3K Β· π) - Detect text blocks and OCR poorly scanned PDFs in bulk. Python.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/aashrafh/Mozart">Mozart</a></b> (π₯10 Β· β 630 Β· π) - An optical music recognition (OMR) system. Converts sheet.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
</details>
<br>
## Data Containers & Structures
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_General-purpose data containers & structures as well as utilities & extensions for pandas._
π <b><a href="https://github.com/ml-tooling/best-of-python#data-containers--dataframes">best-of-python - Data Containers</a></b> ( β 3.7K) - Collection of data-container, dataframe, and pandas-..
<br>
## Data Loading & Extraction
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for loading, collecting, and extracting data from a variety of data sources and formats._
π <b><a href="https://github.com/ml-tooling/best-of-python#data-loading--extraction">best-of-python - Data Extraction</a></b> ( β 3.7K) - Collection of data-loading and -extraction libraries.
<br>
## Web Scraping & Crawling
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for web scraping, crawling, downloading, and mining as well as libraries._
π <b><a href="https://github.com/ml-tooling/best-of-web-python#web-scraping--crawling">best-of-web-python - Web Scraping</a></b> ( β 2.4K) - Collection of web-scraping and crawling libraries.
<br>
## Data Pipelines & Streaming
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for data batch- and stream-processing, workflow automation, job scheduling, and other data pipeline tasks._
π <b><a href="https://github.com/ml-tooling/best-of-python#data-pipelines--streaming">best-of-python - Data Pipelines</a></b> ( β 3.7K) - Libraries for data batch- and stream-processing,..
<br>
## Distributed Machine Learning
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries that provide capabilities to distribute and parallelize machine learning tasks across large-scale compute infrastructure._
<details><summary><b><a href="https://github.com/ray-project/ray">Ray</a></b> (π₯46 Β· β 35K) - Ray is an AI compute engine. Ray consists of a core distributed runtime.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/ray-project/ray) (π¨βπ» 1.1K Β· π 5.9K Β· π₯ 250 Β· π¦ 20K Β· π 20K - 21% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/ray-project/ray
```
- [PyPi](https://pypi.org/project/ray) (π₯ 6.3M / month Β· π¦ 820 Β· β±οΈ 03.12.2024):
```
pip install ray
```
- [Conda](https://anaconda.org/conda-forge/ray-tune) (π₯ 500K Β· β±οΈ 06.12.2024):
```
conda install -c conda-forge ray-tune
```
</details>
<details><summary><b><a href="https://github.com/dask/dask">dask</a></b> (π₯44 Β· β 13K) - Parallel computing with task scheduling. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/dask/dask) (π¨βπ» 610 Β· π 1.7K Β· π¦ 68K Β· π 5.4K - 20% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/dask/dask
```
- [PyPi](https://pypi.org/project/dask) (π₯ 15M / month Β· π¦ 2.6K Β· β±οΈ 17.12.2024):
```
pip install dask
```
- [Conda](https://anaconda.org/conda-forge/dask) (π₯ 12M Β· β±οΈ 17.12.2024):
```
conda install -c conda-forge dask
```
</details>
<details><summary><b><a href="https://github.com/microsoft/DeepSpeed">DeepSpeed</a></b> (π₯41 Β· β 36K) - DeepSpeed is a deep learning optimization library that makes.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/microsoft/DeepSpeed) (π¨βπ» 360 Β· π 4.2K Β· π¦ 10K Β· π 3K - 36% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/microsoft/DeepSpeed
```
- [PyPi](https://pypi.org/project/deepspeed) (π₯ 540K / month Β· π¦ 240 Β· β±οΈ 18.12.2024):
```
pip install deepspeed
```
- [Docker Hub](https://hub.docker.com/r/deepspeed/deepspeed) (π₯ 21K Β· β 4 Β· β±οΈ 02.09.2022):
```
docker pull deepspeed/deepspeed
```
</details>
<details><summary><b><a href="https://github.com/dask/distributed">dask.distributed</a></b> (π₯40 Β· β 1.6K) - A distributed task scheduler for Dask. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/dask/distributed) (π¨βπ» 330 Β· π 720 Β· π¦ 38K Β· π 4K - 39% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/dask/distributed
```
- [PyPi](https://pypi.org/project/distributed) (π₯ 6.3M / month Β· π¦ 890 Β· β±οΈ 17.12.2024):
```
pip install distributed
```
- [Conda](https://anaconda.org/conda-forge/distributed) (π₯ 16M Β· β±οΈ 17.12.2024):
```
conda install -c conda-forge distributed
```
</details>
<details><summary><b><a href="https://github.com/horovod/horovod">horovod</a></b> (π₯36 Β· β 14K) - Distributed training framework for TensorFlow, Keras, PyTorch, and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/horovod/horovod) (π¨βπ» 170 Β· π 2.2K Β· π¦ 1.3K Β· π 2.3K - 17% open Β· β±οΈ 31.08.2024):
```
git clone https://github.com/horovod/horovod
```
- [PyPi](https://pypi.org/project/horovod) (π₯ 93K / month Β· π¦ 33 Β· β±οΈ 12.06.2023):
```
pip install horovod
```
</details>
<details><summary><b><a href="https://github.com/Lightning-AI/torchmetrics">metrics</a></b> (π₯36 Β· β 2.2K) - Machine learning metrics for distributed, scalable PyTorch.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/Lightning-AI/torchmetrics) (π¨βπ» 260 Β· π 400 Β· π₯ 5.9K Β· π¦ 34K Β· π 900 - 8% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/Lightning-AI/metrics
```
- [PyPi](https://pypi.org/project/metrics) (π₯ 4.7K / month Β· π¦ 2 Β· β±οΈ 28.04.2018):
```
pip install metrics
```
- [Conda](https://anaconda.org/conda-forge/torchmetrics) (π₯ 1.7M Β· β±οΈ 12.12.2024):
```
conda install -c conda-forge torchmetrics
```
</details>
<details><summary><b><a href="https://github.com/h2oai/h2o-3">H2O-3</a></b> (π₯34 Β· β 7K) - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/h2oai/h2o-3) (π¨βπ» 270 Β· π 2K Β· π¦ 21 Β· π 9.5K - 29% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/h2oai/h2o-3
```
- [PyPi](https://pypi.org/project/h2o) (π₯ 220K / month Β· π¦ 49 Β· β±οΈ 02.11.2024):
```
pip install h2o
```
</details>
<details><summary><b><a href="https://github.com/hpcaitech/ColossalAI">ColossalAI</a></b> (π₯33 Β· β 39K) - Making large AI models cheaper, faster and more accessible. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/hpcaitech/ColossalAI) (π¨βπ» 190 Β· π 4.4K Β· π¦ 450 Β· π 1.7K - 26% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/hpcaitech/colossalai
```
</details>
<details><summary><b><a href="https://github.com/intel-analytics/ipex-llm">BigDL</a></b> (π₯33 Β· β 6.8K) - Accelerate local LLM inference and finetuning (LLaMA, Mistral,.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/intel-analytics/ipex-llm) (π¨βπ» 110 Β· π 1.3K Β· π₯ 640 Β· π 2.7K - 38% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/intel-analytics/BigDL
```
- [PyPi](https://pypi.org/project/bigdl) (π₯ 31K / month Β· π¦ 2 Β· β±οΈ 24.03.2024):
```
pip install bigdl
```
- [Maven](https://search.maven.org/artifact/com.intel.analytics.bigdl/bigdl-SPARK_2.4) (π¦ 5 Β· β±οΈ 20.04.2021):
```
<dependency>
<groupId>com.intel.analytics.bigdl</groupId>
<artifactId>bigdl-SPARK_2.4</artifactId>
<version>[VERSION]</version>
</dependency>
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/fairscale">FairScale</a></b> (π₯31 Β· β 3.2K Β· π€) - PyTorch extensions for high performance and large scale.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/facebookresearch/fairscale) (π¨βπ» 75 Β· π 280 Β· π¦ 7K Β· π 390 - 26% open Β· β±οΈ 03.05.2024):
```
git clone https://github.com/facebookresearch/fairscale
```
- [PyPi](https://pypi.org/project/fairscale) (π₯ 410K / month Β· π¦ 150 Β· β±οΈ 11.12.2022):
```
pip install fairscale
```
- [Conda](https://anaconda.org/conda-forge/fairscale) (π₯ 350K Β· β±οΈ 28.11.2023):
```
conda install -c conda-forge fairscale
```
</details>
<details><summary><b><a href="https://github.com/mpi4py/mpi4py">mpi4py</a></b> (π₯30 Β· β 820) - Python bindings for MPI. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/mpi4py/mpi4py) (π¨βπ» 27 Β· π 120 Β· π₯ 29K Β· π 190 - 4% open Β· β±οΈ 09.12.2024):
```
git clone https://github.com/mpi4py/mpi4py
```
- [PyPi](https://pypi.org/project/mpi4py) (π₯ 410K / month Β· π¦ 750 Β· β±οΈ 11.10.2024):
```
pip install mpi4py
```
- [Conda](https://anaconda.org/conda-forge/mpi4py) (π₯ 3.2M Β· β±οΈ 12.10.2024):
```
conda install -c conda-forge mpi4py
```
</details>
<details><summary><b><a href="https://github.com/microsoft/SynapseML">SynapseML</a></b> (π₯29 Β· β 5.1K) - Simple and Distributed Machine Learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/microsoft/SynapseML) (π¨βπ» 120 Β· π 830 Β· π 780 - 48% open Β· β±οΈ 02.12.2024):
```
git clone https://github.com/microsoft/SynapseML
```
- [PyPi](https://pypi.org/project/synapseml) (π₯ 260K / month Β· π¦ 5 Β· β±οΈ 16.10.2024):
```
pip install synapseml
```
</details>
<details><summary><b><a href="https://github.com/uber/petastorm">petastorm</a></b> (π₯28 Β· β 1.8K Β· π€) - Petastorm library enables single machine or distributed.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/uber/petastorm) (π¨βπ» 50 Β· π 280 Β· π₯ 540 Β· π¦ 190 Β· π 320 - 53% open Β· β±οΈ 02.12.2023):
```
git clone https://github.com/uber/petastorm
```
- [PyPi](https://pypi.org/project/petastorm) (π₯ 160K / month Β· π¦ 8 Β· β±οΈ 03.02.2023):
```
pip install petastorm
```
</details>
<details><summary><b><a href="https://github.com/facebookincubator/submitit">Submit it</a></b> (π₯28 Β· β 1.3K) - Python 3.8+ toolbox for submitting jobs to Slurm. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/facebookincubator/submitit) (π¨βπ» 25 Β· π 120 Β· π¦ 3.7K Β· π 130 - 38% open Β· β±οΈ 18.09.2024):
```
git clone https://github.com/facebookincubator/submitit
```
- [PyPi](https://pypi.org/project/submitit) (π₯ 430K / month Β· π¦ 49 Β· β±οΈ 18.09.2024):
```
pip install submitit
```
- [Conda](https://anaconda.org/conda-forge/submitit) (π₯ 45K Β· β±οΈ 19.11.2024):
```
conda install -c conda-forge submitit
```
</details>
<details><summary><b><a href="https://github.com/dask/dask-ml">dask-ml</a></b> (π₯28 Β· β 910) - Scalable Machine Learning with Dask. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/dask/dask-ml) (π¨βπ» 80 Β· π 260 Β· π¦ 1.2K Β· π 540 - 52% open Β· β±οΈ 25.11.2024):
```
git clone https://github.com/dask/dask-ml
```
- [PyPi](https://pypi.org/project/dask-ml) (π₯ 130K / month Β· π¦ 93 Β· β±οΈ 02.04.2024):
```
pip install dask-ml
```
- [Conda](https://anaconda.org/conda-forge/dask-ml) (π₯ 930K Β· β±οΈ 17.06.2024):
```
conda install -c conda-forge dask-ml
```
</details>
<details><summary><b><a href="https://github.com/learning-at-home/hivemind">Hivemind</a></b> (π₯25 Β· β 2.1K) - Decentralized deep learning in PyTorch. Built to train models on.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/learning-at-home/hivemind) (π¨βπ» 33 Β· π 170 Β· π¦ 110 Β· π 180 - 43% open Β· β±οΈ 05.11.2024):
```
git clone https://github.com/learning-at-home/hivemind
```
- [PyPi](https://pypi.org/project/hivemind) (π₯ 1.1K / month Β· π¦ 10 Β· β±οΈ 31.08.2023):
```
pip install hivemind
```
</details>
<details><summary><b><a href="https://github.com/apache/singa">Apache Singa</a></b> (π₯24 Β· β 3.4K) - a distributed deep learning platform. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/apache/singa) (π¨βπ» 94 Β· π 1.2K Β· π¦ 5 Β· π 140 - 36% open Β· β±οΈ 29.11.2024):
```
git clone https://github.com/apache/singa
```
- [Conda](https://anaconda.org/nusdbsystem/singa) (π₯ 870 Β· β±οΈ 16.06.2023):
```
conda install -c nusdbsystem singa
```
- [Docker Hub](https://hub.docker.com/r/apache/singa) (π₯ 8.5K Β· β 4 Β· β±οΈ 31.05.2022):
```
docker pull apache/singa
```
</details>
<details><summary><b><a href="https://github.com/microsoft/SynapseML">MMLSpark</a></b> (π₯23 Β· β 5.1K) - Simple and Distributed Machine Learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/microsoft/SynapseML) (π¨βπ» 120 Β· π 830 Β· π 780 - 48% open Β· β±οΈ 02.12.2024):
```
git clone https://github.com/microsoft/SynapseML
```
- [PyPi](https://pypi.org/project/mmlspark) (β±οΈ 18.03.2020):
```
pip install mmlspark
```
</details>
<details><summary><b><a href="https://github.com/intel-analytics/analytics-zoo">analytics-zoo</a></b> (π₯22 Β· β 2.6K) - Distributed Tensorflow, Keras and PyTorch on Apache.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/intel-analytics/analytics-zoo) (π¨βπ» 110 Β· π 730 Β· π 1.3K - 32% open Β· β±οΈ 20.11.2024):
```
git clone https://github.com/intel-analytics/analytics-zoo
```
- [PyPi](https://pypi.org/project/analytics-zoo) (π₯ 2.9K / month Β· π¦ 1 Β· β±οΈ 22.08.2022):
```
pip install analytics-zoo
```
</details>
<details><summary>Show 17 hidden projects...</summary>
- <b><a href="https://github.com/DEAP/deap">DEAP</a></b> (π₯33 Β· β 5.9K) - Distributed Evolutionary Algorithms in Python. <code><a href="http://bit.ly/37RvQcA">βοΈLGPL-3.0</a></code>
- <b><a href="https://github.com/ipython/ipyparallel">ipyparallel</a></b> (π₯31 Β· β 2.6K) - IPython Parallel: Interactive Parallel Computing in.. <code>βUnlicensed</code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/yahoo/TensorFlowOnSpark">TensorFlowOnSpark</a></b> (π₯26 Β· β 3.9K Β· π) - TensorFlowOnSpark brings TensorFlow programs to.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/maxpumperla/elephas">Elephas</a></b> (π₯25 Β· β 1.6K Β· π) - Distributed Deep learning with Keras & Spark. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code>keras</code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/bytedance/byteps">BytePS</a></b> (π₯22 Β· β 3.6K Β· π) - A high performance and generic framework for distributed DNN.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/tensorflow/mesh">Mesh</a></b> (π₯22 Β· β 1.6K Β· π) - Mesh TensorFlow: Model Parallelism Made Easier. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/Ibotta/sk-dist">sk-dist</a></b> (π₯21 Β· β 280 Β· π) - Distributed scikit-learn meta-estimators in PySpark. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/peterwittek/somoclu">somoclu</a></b> (π₯20 Β· β 270 Β· π€) - Massively parallel self-organizing maps: accelerate training on.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/google-deepmind/launchpad">launchpad</a></b> (π₯19 Β· β 320 Β· π) - Launchpad is a library that simplifies writing.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/kingoflolz/mesh-transformer-jax">mesh-transformer-jax</a></b> (π₯18 Β· β 6.3K Β· π) - Model parallel transformers in JAX and Haiku. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/Bluefog-Lib/bluefog">bluefog</a></b> (π₯18 Β· β 300 Β· π) - Distributed and decentralized training framework for PyTorch.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/uber/fiber">Fiber</a></b> (π₯17 Β· β 1K Β· π) - Distributed Computing for AI Made Simple. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/tunib-ai/parallelformers">parallelformers</a></b> (π₯17 Β· β 780 Β· π) - Parallelformers: An Efficient Model Parallelization.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/databricks/tensorframes">TensorFrames</a></b> (π₯16 Β· β 720 Β· π) - Tensorflow wrapper for DataFrames on Apache Spark. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/ml-tooling/lazycluster">LazyCluster</a></b> (π₯14 Β· β 49 Β· π) - Distributed machine learning made simple. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/petuum/autodist">autodist</a></b> (π₯12 Β· β 130 Β· π) - Simple Distributed Deep Learning on TensorFlow. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/facebookresearch/moolib">moolib</a></b> (π₯11 Β· β 370 Β· π) - A library for distributed ML training with PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
</details>
<br>
## Hyperparameter Optimization & AutoML
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for hyperparameter optimization, automl and neural architecture search._
<details><summary><b><a href="https://github.com/optuna/optuna">Optuna</a></b> (π₯43 Β· β 11K) - A hyperparameter optimization framework. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/optuna/optuna) (π¨βπ» 280 Β· π 1K Β· π¦ 20K Β· π 1.7K - 3% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/optuna/optuna
```
- [PyPi](https://pypi.org/project/optuna) (π₯ 4M / month Β· π¦ 1K Β· β±οΈ 12.11.2024):
```
pip install optuna
```
- [Conda](https://anaconda.org/conda-forge/optuna) (π₯ 2M Β· β±οΈ 13.11.2024):
```
conda install -c conda-forge optuna
```
</details>
<details><summary><b><a href="https://github.com/autogluon/autogluon">AutoGluon</a></b> (π₯36 Β· β 8.2K) - Fast and Accurate ML in 3 Lines of Code. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/autogluon/autogluon) (π¨βπ» 130 Β· π 940 Β· π¦ 910 Β· π 1.5K - 24% open Β· β±οΈ 11.12.2024):
```
git clone https://github.com/autogluon/autogluon
```
- [PyPi](https://pypi.org/project/autogluon) (π₯ 190K / month Β· π¦ 28 Β· β±οΈ 19.12.2024):
```
pip install autogluon
```
- [Conda](https://anaconda.org/conda-forge/autogluon) (π₯ 25K Β· β±οΈ 12.12.2024):
```
conda install -c conda-forge autogluon
```
- [Docker Hub](https://hub.docker.com/r/autogluon/autogluon) (π₯ 12K Β· β 17 Β· β±οΈ 07.03.2024):
```
docker pull autogluon/autogluon
```
</details>
<details><summary><b><a href="https://github.com/facebook/Ax">Ax</a></b> (π₯36 Β· β 2.4K) - Adaptive Experimentation Platform. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/facebook/Ax) (π¨βπ» 180 Β· π 310 Β· π¦ 860 Β· π 800 - 9% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/facebook/Ax
```
- [PyPi](https://pypi.org/project/ax-platform) (π₯ 120K / month Β· π¦ 54 Β· β±οΈ 23.09.2024):
```
pip install ax-platform
```
- [Conda](https://anaconda.org/conda-forge/ax-platform) (π₯ 31K Β· β±οΈ 24.09.2024):
```
conda install -c conda-forge ax-platform
```
</details>
<details><summary><b><a href="https://github.com/pytorch/botorch">BoTorch</a></b> (π₯34 Β· β 3.1K) - Bayesian optimization in PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pytorch/botorch) (π¨βπ» 140 Β· π 400 Β· π¦ 1.3K Β· π 560 - 14% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/pytorch/botorch
```
- [PyPi](https://pypi.org/project/botorch) (π₯ 180K / month Β· π¦ 84 Β· β±οΈ 17.09.2024):
```
pip install botorch
```
- [Conda](https://anaconda.org/conda-forge/botorch) (π₯ 130K Β· β±οΈ 20.09.2024):
```
conda install -c conda-forge botorch
```
</details>
<details><summary><b><a href="https://github.com/hyperopt/hyperopt">Hyperopt</a></b> (π₯33 Β· β 7.3K) - Distributed Asynchronous Hyperparameter Optimization in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/hyperopt/hyperopt) (π¨βπ» 100 Β· π 1.1K Β· π¦ 18K Β· π 690 - 20% open Β· β±οΈ 25.09.2024):
```
git clone https://github.com/hyperopt/hyperopt
```
- [PyPi](https://pypi.org/project/hyperopt) (π₯ 2.5M / month Β· π¦ 450 Β· β±οΈ 17.11.2021):
```
pip install hyperopt
```
- [Conda](https://anaconda.org/conda-forge/hyperopt) (π₯ 800K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge hyperopt
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/nevergrad">nevergrad</a></b> (π₯33 Β· β 4K) - A Python toolbox for performing gradient-free optimization. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/facebookresearch/nevergrad) (π¨βπ» 57 Β· π 360 Β· π¦ 800 Β· π 310 - 39% open Β· β±οΈ 05.12.2024):
```
git clone https://github.com/facebookresearch/nevergrad
```
- [PyPi](https://pypi.org/project/nevergrad) (π₯ 130K / month Β· π¦ 62 Β· β±οΈ 01.12.2024):
```
pip install nevergrad
```
- [Conda](https://anaconda.org/conda-forge/nevergrad) (π₯ 57K Β· β±οΈ 09.01.2024):
```
conda install -c conda-forge nevergrad
```
</details>
<details><summary><b><a href="https://github.com/keras-team/autokeras">AutoKeras</a></b> (π₯32 Β· β 9.2K) - AutoML library for deep learning. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/keras-team/autokeras) (π¨βπ» 140 Β· π 1.4K Β· π₯ 19K Β· π¦ 780 Β· π 900 - 16% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/keras-team/autokeras
```
- [PyPi](https://pypi.org/project/autokeras) (π₯ 26K / month Β· π¦ 13 Β· β±οΈ 20.03.2024):
```
pip install autokeras
```
</details>
<details><summary><b><a href="https://github.com/bayesian-optimization/BayesianOptimization">Bayesian Optimization</a></b> (π₯32 Β· β 8K) - A Python implementation of global optimization with.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/bayesian-optimization/BayesianOptimization) (π¨βπ» 47 Β· π 1.6K Β· π₯ 170 Β· π¦ 3.2K Β· π 370 - 2% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/fmfn/BayesianOptimization
```
- [PyPi](https://pypi.org/project/bayesian-optimization) (π₯ 420K / month Β· π¦ 150 Β· β±οΈ 18.12.2024):
```
pip install bayesian-optimization
```
</details>
<details><summary><b><a href="https://github.com/alteryx/featuretools">featuretools</a></b> (π₯31 Β· β 7.3K) - An open source python library for automated feature engineering. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/alteryx/featuretools) (π¨βπ» 74 Β· π 880 Β· π¦ 1.9K Β· π 1K - 15% open Β· β±οΈ 13.11.2024):
```
git clone https://github.com/alteryx/featuretools
```
- [PyPi](https://pypi.org/project/featuretools) (π₯ 62K / month Β· π¦ 74 Β· β±οΈ 14.05.2024):
```
pip install featuretools
```
- [Conda](https://anaconda.org/conda-forge/featuretools) (π₯ 220K Β· β±οΈ 15.05.2024):
```
conda install -c conda-forge featuretools
```
</details>
<details><summary><b><a href="https://github.com/keras-team/keras-tuner">Keras Tuner</a></b> (π₯31 Β· β 2.9K) - A Hyperparameter Tuning Library for Keras. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/keras-team/keras-tuner) (π¨βπ» 61 Β· π 400 Β· π¦ 4.8K Β· π 490 - 44% open Β· β±οΈ 24.06.2024):
```
git clone https://github.com/keras-team/keras-tuner
```
- [PyPi](https://pypi.org/project/keras-tuner) (π₯ 380K / month Β· π¦ 120 Β· β±οΈ 04.03.2024):
```
pip install keras-tuner
```
- [Conda](https://anaconda.org/conda-forge/keras-tuner) (π₯ 45K Β· β±οΈ 05.03.2024):
```
conda install -c conda-forge keras-tuner
```
</details>
<details><summary><b><a href="https://github.com/mljar/mljar-supervised">mljar-supervised</a></b> (π₯30 Β· β 3.1K) - Python package for AutoML on Tabular Data with Feature.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/mljar/mljar-supervised) (π¨βπ» 29 Β· π 410 Β· π¦ 140 Β· π 660 - 21% open Β· β±οΈ 26.11.2024):
```
git clone https://github.com/mljar/mljar-supervised
```
- [PyPi](https://pypi.org/project/mljar-supervised) (π₯ 11K / month Β· π¦ 6 Β· β±οΈ 12.11.2024):
```
pip install mljar-supervised
```
- [Conda](https://anaconda.org/conda-forge/mljar-supervised) (π₯ 27K Β· β±οΈ 12.11.2024):
```
conda install -c conda-forge mljar-supervised
```
</details>
<details><summary><b><a href="https://github.com/shankarpandala/lazypredict">lazypredict</a></b> (π₯30 Β· β 3K) - Lazy Predict help build a lot of basic models without much code.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/shankarpandala/lazypredict) (π¨βπ» 18 Β· π 350 Β· π¦ 1.2K Β· π 140 - 70% open Β· β±οΈ 03.11.2024):
```
git clone https://github.com/shankarpandala/lazypredict
```
- [PyPi](https://pypi.org/project/lazypredict) (π₯ 17K / month Β· π¦ 6 Β· β±οΈ 02.11.2024):
```
pip install lazypredict
```
- [Conda](https://anaconda.org/conda-forge/lazypredict) (π₯ 3.9K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge lazypredict
```
</details>
<details><summary><b><a href="https://github.com/autonomio/talos">Talos</a></b> (π₯25 Β· β 1.6K Β· π€) - Hyperparameter Experiments with TensorFlow and Keras. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/autonomio/talos) (π¨βπ» 23 Β· π 270 Β· π¦ 190 Β· π 400 - 2% open Β· β±οΈ 22.04.2024):
```
git clone https://github.com/autonomio/talos
```
- [PyPi](https://pypi.org/project/talos) (π₯ 1.6K / month Β· π¦ 8 Β· β±οΈ 21.04.2024):
```
pip install talos
```
</details>
<details><summary><b><a href="https://github.com/aimclub/FEDOT">FEDOT</a></b> (π₯24 Β· β 650) - Automated modeling and machine learning framework FEDOT. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/aimclub/FEDOT) (π¨βπ» 36 Β· π 88 Β· π¦ 55 Β· π 550 - 10% open Β· β±οΈ 15.11.2024):
```
git clone https://github.com/nccr-itmo/FEDOT
```
- [PyPi](https://pypi.org/project/fedot) (π₯ 1.6K / month Β· π¦ 5 Β· β±οΈ 28.08.2024):
```
pip install fedot
```
</details>
<details><summary><b><a href="https://github.com/SimonBlanke/Hyperactive">Hyperactive</a></b> (π₯24 Β· β 520) - An optimization and data collection toolbox for convenient and fast.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/SimonBlanke/Hyperactive) (π¨βπ» 9 Β· π 42 Β· π₯ 290 Β· π¦ 36 Β· π 77 - 18% open Β· β±οΈ 13.11.2024):
```
git clone https://github.com/SimonBlanke/Hyperactive
```
- [PyPi](https://pypi.org/project/hyperactive) (π₯ 2.9K / month Β· π¦ 13 Β· β±οΈ 15.08.2024):
```
pip install hyperactive
```
</details>
<details><summary><b><a href="https://github.com/AutoViML/featurewiz">featurewiz</a></b> (π₯21 Β· β 600 Β· π€) - Use advanced feature engineering strategies and select best.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/AutoViML/featurewiz) (π¨βπ» 18 Β· π 90 Β· π¦ 79 Β· π 100 - 8% open Β· β±οΈ 02.05.2024):
```
git clone https://github.com/AutoViML/featurewiz
```
- [PyPi](https://pypi.org/project/featurewiz) (π₯ 59K / month Β· π¦ 2 Β· β±οΈ 10.02.2024):
```
pip install featurewiz
```
</details>
<details><summary><b><a href="https://github.com/ScottfreeLLC/AlphaPy">AlphaPy</a></b> (π₯20 Β· β 1.2K) - Python AutoML for Trading Systems and Sports Betting. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/ScottfreeLLC/AlphaPy) (π¨βπ» 5 Β· π 200 Β· π¦ 6 Β· π 42 - 30% open Β· β±οΈ 15.12.2024):
```
git clone https://github.com/ScottfreeLLC/AlphaPy
```
- [PyPi](https://pypi.org/project/alphapy) (π₯ 910 / month Β· β±οΈ 29.08.2020):
```
pip install alphapy
```
</details>
<details><summary><b><a href="https://github.com/gugarosa/opytimizer">opytimizer</a></b> (π₯20 Β· β 610) - Opytimizer is a Python library consisting of meta-heuristic.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/gugarosa/opytimizer) (π¨βπ» 4 Β· π 42 Β· π¦ 19 Β· β±οΈ 18.08.2024):
```
git clone https://github.com/gugarosa/opytimizer
```
- [PyPi](https://pypi.org/project/opytimizer) (π₯ 400 / month Β· β±οΈ 18.08.2024):
```
pip install opytimizer
```
</details>
<details><summary><b><a href="https://github.com/AutoViML/Auto_ViML">Auto ViML</a></b> (π₯20 Β· β 530 Β· π€) - Automatically Build Multiple ML Models with a Single Line of.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/AutoViML/Auto_ViML) (π¨βπ» 9 Β· π 100 Β· π¦ 27 Β· π 34 - 2% open Β· β±οΈ 11.05.2024):
```
git clone https://github.com/AutoViML/Auto_ViML
```
- [PyPi](https://pypi.org/project/autoviml) (π₯ 7.5K / month Β· π¦ 3 Β· β±οΈ 11.05.2024):
```
pip install autoviml
```
</details>
<details><summary><b><a href="https://github.com/cerlymarco/shap-hypetune">shap-hypetune</a></b> (π₯18 Β· β 570 Β· π€) - A python package for simultaneous Hyperparameters Tuning and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/cerlymarco/shap-hypetune) (π¨βπ» 3 Β· π 69 Β· π¦ 20 Β· π 36 - 11% open Β· β±οΈ 21.02.2024):
```
git clone https://github.com/cerlymarco/shap-hypetune
```
- [PyPi](https://pypi.org/project/shap-hypetune) (π₯ 2.4K / month Β· π¦ 2 Β· β±οΈ 21.02.2024):
```
pip install shap-hypetune
```
</details>
<details><summary>Show 32 hidden projects...</summary>
- <b><a href="https://github.com/scikit-optimize/scikit-optimize">scikit-optimize</a></b> (π₯32 Β· β 2.7K Β· π) - Sequential model-based optimization with a.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/microsoft/nni">NNI</a></b> (π₯31 Β· β 14K Β· π) - An open source AutoML toolkit for automate machine learning lifecycle,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/EpistasisLab/tpot">TPOT</a></b> (π₯31 Β· β 9.8K Β· π€) - A Python Automated Machine Learning tool that optimizes.. <code><a href="http://bit.ly/37RvQcA">βοΈLGPL-3.0</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/automl/auto-sklearn">auto-sklearn</a></b> (π₯31 Β· β 7.7K Β· π) - Automated Machine Learning with scikit-learn. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/maxpumperla/hyperas">Hyperas</a></b> (π₯27 Β· β 2.2K Β· π) - Keras + Hyperopt: A very simple wrapper for convenient.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/automl/SMAC3">SMAC3</a></b> (π₯26 Β· β 1.1K) - SMAC3: A Versatile Bayesian Optimization Package for.. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">βοΈBSD-1-Clause</a></code>
- <b><a href="https://github.com/SheffieldML/GPyOpt">GPyOpt</a></b> (π₯26 Β· β 930 Β· π) - Gaussian Process Optimization using GPy. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/tensorflow/adanet">AdaNet</a></b> (π₯24 Β· β 3.5K Β· π) - Fast and flexible AutoML with learning guarantees. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/ClimbsRocks/auto_ml">auto_ml</a></b> (π₯24 Β· β 1.6K Β· π) - [UNMAINTAINED] Automated machine learning for analytics & production. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/mindsdb/lightwood">lightwood</a></b> (π₯24 Β· β 450) - Lightwood is Legos for Machine Learning. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/automl/HpBandSter">HpBandSter</a></b> (π₯22 Β· β 610 Β· π) - a distributed Hyperband implementation on Steroids. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/Epistimio/orion">Orion</a></b> (π₯22 Β· β 290 Β· π) - Asynchronous Distributed Hyperparameter Optimization. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/nidhaloff/igel">igel</a></b> (π₯21 Β· β 3.1K Β· π) - a delightful machine learning tool that allows you to train, test, and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/AxeldeRomblay/MLBox">MLBox</a></b> (π₯21 Β· β 1.5K Β· π) - MLBox is a powerful Automated Machine Learning python library. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">βοΈBSD-1-Clause</a></code>
- <b><a href="https://github.com/rsteca/sklearn-deap">sklearn-deap</a></b> (π₯21 Β· β 770 Β· π) - Use evolutionary algorithms instead of gridsearch in.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/williamFalcon/test-tube">Test Tube</a></b> (π₯21 Β· β 740 Β· π) - Python library to easily log experiments and parallelize.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/Neuraxio/Neuraxle">Neuraxle</a></b> (π₯21 Β· β 610 Β· π) - The worlds cleanest AutoML library - Do hyperparameter tuning.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/claesenm/optunity">optunity</a></b> (π₯21 Β· β 420 Β· π) - optimization routines for hyperparameter tuning. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/dragonfly/dragonfly">Dragonfly</a></b> (π₯19 Β· β 860 Β· π) - An open source python library for scalable Bayesian optimisation. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/HDI-Project/ATM">Auto Tune Models</a></b> (π₯19 Β· β 530 Β· π) - Auto Tune Models - A multi-tenant, multi-data system for.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/sherpa-ai/sherpa">Sherpa</a></b> (π₯19 Β· β 330 Β· π) - Hyperparameter optimization that enables researchers to.. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/tobegit3hub/advisor">Advisor</a></b> (π₯18 Β· β 1.6K Β· π) - Open-source implementation of Google Vizier for hyper parameters.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/reiinakano/xcessiv">Xcessiv</a></b> (π₯18 Β· β 1.3K Β· π) - A web-based application for quick, scalable, and automated.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/HunterMcGushion/hyperparameter_hunter">HyperparameterHunter</a></b> (π₯17 Β· β 700 Β· π) - Easy hyperparameter optimization and automatic result.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/minimaxir/automl-gs">automl-gs</a></b> (π₯16 Β· β 1.9K Β· π) - Provide an input CSV and a target field to predict, generate a.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/jmcarpenter2/parfit">Parfit</a></b> (π₯15 Β· β 200 Β· π) - A package for parallelizing the fit and flexibly scoring of.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/carpedm20/ENAS-pytorch">ENAS</a></b> (π₯13 Β· β 2.7K Β· π) - PyTorch implementation of Efficient Neural Architecture Search via.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/LGE-ARC-AdvancedAI/auptimizer">Auptimizer</a></b> (π₯13 Β· β 200 Β· π) - An automatic ML model optimization tool. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/genixpro/hypermax">Hypermax</a></b> (π₯12 Β· β 110 Β· π€) - Better, faster hyper-parameter optimization. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/google/model_search">model_search</a></b> (π₯11 Β· β 3.3K Β· π) - AutoML algorithms for model architecture search at scale. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/joeddav/devol">Devol</a></b> (π₯11 Β· β 950 Β· π) - Genetic neural architecture search with Keras. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/gdikov/hypertunity">Hypertunity</a></b> (π₯10 Β· β 140 Β· π) - A toolset for black-box hyperparameter optimisation. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
</details>
<br>
## Reinforcement Learning
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for building and evaluating reinforcement learning & agent-based systems._
<details><summary><b><a href="https://github.com/AI4Finance-Foundation/FinRL">FinRL</a></b> (π₯31 Β· β 10K) - FinRL: Financial Reinforcement Learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/AI4Finance-Foundation/FinRL) (π¨βπ» 120 Β· π 2.4K Β· π¦ 56 Β· π 720 - 33% open Β· β±οΈ 13.12.2024):
```
git clone https://github.com/AI4Finance-Foundation/FinRL
```
- [PyPi](https://pypi.org/project/finrl) (π₯ 1.5K / month Β· β±οΈ 08.01.2022):
```
pip install finrl
```
</details>
<details><summary><b><a href="https://github.com/google/dopamine">Dopamine</a></b> (π₯28 Β· β 11K) - Dopamine is a research framework for fast prototyping of.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/google/dopamine) (π¨βπ» 15 Β· π 1.4K Β· π¦ 21 Β· π 190 - 54% open Β· β±οΈ 04.11.2024):
```
git clone https://github.com/google/dopamine
```
- [PyPi](https://pypi.org/project/dopamine-rl) (π₯ 25K / month Β· π¦ 10 Β· β±οΈ 31.10.2024):
```
pip install dopamine-rl
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/agents">TF-Agents</a></b> (π₯28 Β· β 2.8K) - TF-Agents: A reliable, scalable and easy to use TensorFlow.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/agents) (π¨βπ» 150 Β· π 720 Β· π 670 - 29% open Β· β±οΈ 12.12.2024):
```
git clone https://github.com/tensorflow/agents
```
- [PyPi](https://pypi.org/project/tf-agents) (π₯ 36K / month Β· π¦ 14 Β· β±οΈ 14.12.2023):
```
pip install tf-agents
```
</details>
<details><summary><b><a href="https://github.com/Farama-Foundation/ViZDoom">ViZDoom</a></b> (π₯28 Β· β 1.8K) - Reinforcement Learning environments based on the 1993 game Doom. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/Farama-Foundation/ViZDoom) (π¨βπ» 55 Β· π 390 Β· π₯ 12K Β· π¦ 280 Β· π 460 - 6% open Β· β±οΈ 08.09.2024):
```
git clone https://github.com/mwydmuch/ViZDoom
```
- [PyPi](https://pypi.org/project/vizdoom) (π₯ 5.7K / month Β· π¦ 15 Β· β±οΈ 20.08.2024):
```
pip install vizdoom
```
</details>
<details><summary><b><a href="https://github.com/google-deepmind/acme">Acme</a></b> (π₯27 Β· β 3.5K) - A library of reinforcement learning components and agents. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/google-deepmind/acme) (π¨βπ» 86 Β· π 430 Β· π¦ 220 Β· π 270 - 23% open Β· β±οΈ 30.10.2024):
```
git clone https://github.com/deepmind/acme
```
- [PyPi](https://pypi.org/project/dm-acme) (π₯ 1.7K / month Β· π¦ 3 Β· β±οΈ 10.02.2022):
```
pip install dm-acme
```
- [Conda](https://anaconda.org/conda-forge/dm-acme) (π₯ 11K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge dm-acme
```
</details>
<details><summary><b><a href="https://github.com/tensorforce/tensorforce">TensorForce</a></b> (π₯26 Β· β 3.3K) - Tensorforce: a TensorFlow library for applied.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorforce/tensorforce) (π¨βπ» 85 Β· π 530 Β· π¦ 460 Β· π 680 - 6% open Β· β±οΈ 31.07.2024):
```
git clone https://github.com/tensorforce/tensorforce
```
- [PyPi](https://pypi.org/project/tensorforce) (π₯ 880 / month Β· π¦ 4 Β· β±οΈ 30.08.2021):
```
pip install tensorforce
```
</details>
<details><summary><b><a href="https://github.com/PaddlePaddle/PARL">PARL</a></b> (π₯25 Β· β 3.3K) - A high-performance distributed training framework for Reinforcement.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/PaddlePaddle/PARL) (π¨βπ» 45 Β· π 810 Β· π¦ 130 Β· π 540 - 24% open Β· β±οΈ 09.07.2024):
```
git clone https://github.com/PaddlePaddle/PARL
```
- [PyPi](https://pypi.org/project/parl) (π₯ 1.4K / month Β· π¦ 1 Β· β±οΈ 13.05.2022):
```
pip install parl
```
</details>
<details><summary><b><a href="https://github.com/google-deepmind/rlax">RLax</a></b> (π₯24 Β· β 1.3K Β· π€) - A library of reinforcement learning building blocks in JAX. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/google-deepmind/rlax) (π¨βπ» 21 Β· π 87 Β· π¦ 290 Β· π 26 - 30% open Β· β±οΈ 24.05.2024):
```
git clone https://github.com/deepmind/rlax
```
- [PyPi](https://pypi.org/project/rlax) (π₯ 22K / month Β· π¦ 11 Β· β±οΈ 09.01.2023):
```
pip install rlax
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/ReAgent">ReAgent</a></b> (π₯22 Β· β 3.6K) - A platform for Reasoning systems (Reinforcement Learning,.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/facebookresearch/ReAgent) (π¨βπ» 170 Β· π 510 Β· π 160 - 53% open Β· β±οΈ 26.11.2024):
```
git clone https://github.com/facebookresearch/ReAgent
```
- [PyPi](https://pypi.org/project/reagent) (π₯ 42 / month Β· β±οΈ 27.05.2020):
```
pip install reagent
```
</details>
<details><summary><b><a href="https://github.com/pfnet/pfrl">PFRL</a></b> (π₯22 Β· β 1.2K) - PFRL: a PyTorch-based deep reinforcement learning library. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/pfnet/pfrl) (π¨βπ» 20 Β· π 150 Β· π¦ 120 Β· π 79 - 41% open Β· β±οΈ 04.08.2024):
```
git clone https://github.com/pfnet/pfrl
```
- [PyPi](https://pypi.org/project/pfrl) (π₯ 580 / month Β· π¦ 1 Β· β±οΈ 16.07.2023):
```
pip install pfrl
```
</details>
<details><summary><b><a href="https://github.com/google-research/rliable">rliable</a></b> (π₯13 Β· β 790) - [NeurIPS21 Outstanding Paper] Library for reliable evaluation on RL.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/google-research/rliable) (π¨βπ» 9 Β· π 48 Β· π¦ 170 Β· π 19 - 15% open Β· β±οΈ 12.08.2024):
```
git clone https://github.com/google-research/rliable
```
- [PyPi](https://pypi.org/project/rliable`):
```
pip install rliable`
```
</details>
<details><summary>Show 12 hidden projects...</summary>
- <b><a href="https://github.com/openai/gym">OpenAI Gym</a></b> (π₯40 Β· β 35K Β· π) - A toolkit for developing and comparing reinforcement learning.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/openai/baselines">baselines</a></b> (π₯29 Β· β 16K Β· π) - OpenAI Baselines: high-quality implementations of reinforcement.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/keras-rl/keras-rl">keras-rl</a></b> (π₯28 Β· β 5.5K Β· π) - Deep Reinforcement Learning for Keras. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/tensorlayer/TensorLayer">TensorLayer</a></b> (π₯27 Β· β 7.3K Β· π) - Deep Learning and Reinforcement Learning Library for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/rlworkgroup/garage">garage</a></b> (π₯25 Β· β 1.9K Β· π) - A toolkit for reproducible reinforcement learning research. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/hill-a/stable-baselines">Stable Baselines</a></b> (π₯24 Β· β 4.2K Β· π) - A fork of OpenAI Baselines, implementations of.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/chainer/chainerrl">ChainerRL</a></b> (π₯24 Β· β 1.2K Β· π) - ChainerRL is a deep reinforcement learning library built on top of.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/google-deepmind/trfl">TRFL</a></b> (π₯22 Β· β 3.1K Β· π) - TensorFlow Reinforcement Learning. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/IntelLabs/coach">Coach</a></b> (π₯20 Β· β 2.3K Β· π) - Reinforcement Learning Coach by Intel AI Lab enables easy.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/SerpentAI/SerpentAI">SerpentAI</a></b> (π₯19 Β· β 6.8K Β· π) - Game Agent Framework. Helping you create AIs / Bots that learn to.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/google-deepmind/lab">DeepMind Lab</a></b> (π₯17 Β· β 7.1K Β· π) - A customisable 3D platform for agent-based AI research. <code>βUnlicensed</code>
- <b><a href="https://github.com/enlite-ai/maze">Maze</a></b> (π₯13 Β· β 270 Β· π) - Maze Applied Reinforcement Learning Framework. <code><a href="https://tldrlegal.com/search?q=Custom">βοΈCustom</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
</details>
<br>
## Recommender Systems
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for building and evaluating recommendation systems._
<details><summary><b><a href="https://github.com/recommenders-team/recommenders">Recommenders</a></b> (π₯33 Β· β 19K) - Best Practices on Recommendation Systems. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/recommenders-team/recommenders) (π¨βπ» 140 Β· π 3.1K Β· π₯ 640 Β· π¦ 140 Β· π 870 - 18% open Β· β±οΈ 15.11.2024):
```
git clone https://github.com/microsoft/recommenders
```
- [PyPi](https://pypi.org/project/recommenders) (π₯ 39K / month Β· π¦ 4 Β· β±οΈ 01.05.2024):
```
pip install recommenders
```
</details>
<details><summary><b><a href="https://github.com/pytorch/torchrec">torchrec</a></b> (π₯31 Β· β 2K) - Pytorch domain library for recommendation systems. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/pytorch/torchrec) (π¨βπ» 300 Β· π 440 Β· π¦ 160 Β· π 440 - 72% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/pytorch/torchrec
```
- [PyPi](https://pypi.org/project/torchrec-nightly-cpu) (π₯ 26K / month Β· β±οΈ 12.05.2022):
```
pip install torchrec-nightly-cpu
```
</details>
<details><summary><b><a href="https://github.com/NicolasHug/Surprise">scikit-surprise</a></b> (π₯27 Β· β 6.4K) - A Python scikit for building and analyzing recommender.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/NicolasHug/Surprise) (π¨βπ» 46 Β· π 1K Β· π¦ 21 Β· π 400 - 21% open Β· β±οΈ 14.06.2024):
```
git clone https://github.com/NicolasHug/Surprise
```
- [PyPi](https://pypi.org/project/scikit-surprise) (π₯ 110K / month Β· π¦ 37 Β· β±οΈ 19.05.2024):
```
pip install scikit-surprise
```
- [Conda](https://anaconda.org/conda-forge/scikit-surprise) (π₯ 440K Β· β±οΈ 20.05.2024):
```
conda install -c conda-forge scikit-surprise
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/ranking">TF Ranking</a></b> (π₯26 Β· β 2.7K Β· π€) - Learning to Rank in TensorFlow. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/ranking) (π¨βπ» 36 Β· π 480 Β· π 330 - 27% open Β· β±οΈ 18.03.2024):
```
git clone https://github.com/tensorflow/ranking
```
- [PyPi](https://pypi.org/project/tensorflow_ranking) (π₯ 74K / month Β· π¦ 15 Β· β±οΈ 18.03.2024):
```
pip install tensorflow_ranking
```
</details>
<details><summary><b><a href="https://github.com/PreferredAI/cornac">Cornac</a></b> (π₯26 Β· β 900) - A Comparative Framework for Multimodal Recommender Systems. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/PreferredAI/cornac) (π¨βπ» 22 Β· π 140 Β· π¦ 250 Β· π 160 - 14% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/PreferredAI/cornac
```
- [PyPi](https://pypi.org/project/cornac) (π₯ 42K / month Β· π¦ 18 Β· β±οΈ 15.08.2024):
```
pip install cornac
```
- [Conda](https://anaconda.org/conda-forge/cornac) (π₯ 630K Β· β±οΈ 13.09.2024):
```
conda install -c conda-forge cornac
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/recommenders">TF Recommenders</a></b> (π₯25 Β· β 1.9K) - TensorFlow Recommenders is a library for building.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/recommenders) (π¨βπ» 43 Β· π 280 Β· π 450 - 59% open Β· β±οΈ 05.12.2024):
```
git clone https://github.com/tensorflow/recommenders
```
- [PyPi](https://pypi.org/project/tensorflow-recommenders) (π₯ 310K / month Β· π¦ 2 Β· β±οΈ 03.02.2023):
```
pip install tensorflow-recommenders
```
</details>
<details><summary><b><a href="https://github.com/RUCAIBox/RecBole">RecBole</a></b> (π₯24 Β· β 3.5K) - A unified, comprehensive and efficient recommendation library. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/RUCAIBox/RecBole) (π¨βπ» 74 Β· π 620 Β· π 1K - 28% open Β· β±οΈ 05.09.2024):
```
git clone https://github.com/RUCAIBox/RecBole
```
- [PyPi](https://pypi.org/project/recbole) (π₯ 57K / month Β· π¦ 2 Β· β±οΈ 31.10.2023):
```
pip install recbole
```
- [Conda](https://anaconda.org/aibox/recbole) (π₯ 6.8K Β· β±οΈ 01.11.2023):
```
conda install -c aibox recbole
```
</details>
<details><summary>Show 10 hidden projects...</summary>
- <b><a href="https://github.com/benfred/implicit">implicit</a></b> (π₯29 Β· β 3.6K Β· π) - Fast Python Collaborative Filtering for Implicit Feedback Datasets. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/lyst/lightfm">lightfm</a></b> (π₯28 Β· β 4.8K Β· π) - A Python implementation of LightFM, a hybrid recommendation.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/lenskit/lkpy">lkpy</a></b> (π₯25 Β· β 270) - Python recommendation toolkit. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/ibayer/fastFM">fastFM</a></b> (π₯22 Β· β 1.1K Β· π) - fastFM: A Library for Factorization Machines. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/jfkirk/tensorrec">tensorrec</a></b> (π₯21 Β· β 1.3K Β· π) - A TensorFlow recommendation algorithm and framework in.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/statisticianinstilettos/recmetrics">recmetrics</a></b> (π₯19 Β· β 570 Β· π) - A library of metrics for evaluating recommender systems. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/maciejkula/spotlight">Spotlight</a></b> (π₯18 Β· β 3K Β· π) - Deep recommender models using PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/caserec/CaseRecommender">Case Recommender</a></b> (π₯18 Β· β 490 Β· π) - Case Recommender: A Flexible and Extensible Python.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/ShopRunner/collie">Collie</a></b> (π₯17 Β· β 110 Β· π) - A library for preparing, training, and evaluating scalable deep.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/ylongqi/openrec">OpenRec</a></b> (π₯16 Β· β 410 Β· π) - OpenRec is an open-source and modular library for neural network-.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
</details>
<br>
## Privacy Machine Learning
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for encrypted and privacy-preserving machine learning using methods like federated learning & differential privacy._
<details><summary><b><a href="https://github.com/OpenMined/PySyft">PySyft</a></b> (π₯36 Β· β 9.6K) - Perform data science on data that remains in someone elses server. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/OpenMined/PySyft) (π¨βπ» 520 Β· π 2K Β· π₯ 2.4K Β· π¦ 1 Β· π 3.4K - 1% open Β· β±οΈ 03.11.2024):
```
git clone https://github.com/OpenMined/PySyft
```
- [PyPi](https://pypi.org/project/syft) (π₯ 12K / month Β· π¦ 4 Β· β±οΈ 03.11.2024):
```
pip install syft
```
</details>
<details><summary><b><a href="https://github.com/pytorch/opacus">Opacus</a></b> (π₯31 Β· β 1.7K) - Training PyTorch models with differential privacy. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pytorch/opacus) (π¨βπ» 82 Β· π 340 Β· π₯ 140 Β· π¦ 930 Β· π 320 - 22% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/pytorch/opacus
```
- [PyPi](https://pypi.org/project/opacus) (π₯ 100K / month Β· π¦ 36 Β· β±οΈ 03.08.2024):
```
pip install opacus
```
- [Conda](https://anaconda.org/conda-forge/opacus) (π₯ 19K Β· β±οΈ 05.08.2024):
```
conda install -c conda-forge opacus
```
</details>
<details><summary><b><a href="https://github.com/FederatedAI/FATE">FATE</a></b> (π₯26 Β· β 5.8K) - An Industrial Grade Federated Learning Framework. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/FederatedAI/FATE) (π¨βπ» 100 Β· π 1.6K Β· π 2.1K - 3% open Β· β±οΈ 19.11.2024):
```
git clone https://github.com/FederatedAI/FATE
```
- [PyPi](https://pypi.org/project/ETAF) (β±οΈ 06.05.2020):
```
pip install ETAF
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/privacy">TensorFlow Privacy</a></b> (π₯25 Β· β 1.9K) - Library for training machine learning models with.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/privacy) (π¨βπ» 59 Β· π 440 Β· π₯ 180 Β· π 210 - 55% open Β· β±οΈ 25.11.2024):
```
git clone https://github.com/tensorflow/privacy
```
- [PyPi](https://pypi.org/project/tensorflow-privacy) (π₯ 20K / month Β· π¦ 21 Β· β±οΈ 14.02.2024):
```
pip install tensorflow-privacy
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/CrypTen">CrypTen</a></b> (π₯24 Β· β 1.6K) - A framework for Privacy Preserving Machine Learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/facebookresearch/CrypTen) (π¨βπ» 39 Β· π 280 Β· π¦ 47 Β· π 280 - 28% open Β· β±οΈ 23.11.2024):
```
git clone https://github.com/facebookresearch/CrypTen
```
- [PyPi](https://pypi.org/project/crypten) (π₯ 400 / month Β· π¦ 1 Β· β±οΈ 08.12.2022):
```
pip install crypten
```
</details>
<details><summary><b><a href="https://github.com/tf-encrypted/tf-encrypted">TFEncrypted</a></b> (π₯23 Β· β 1.2K) - A Framework for Encrypted Machine Learning in TensorFlow. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tf-encrypted/tf-encrypted) (π¨βπ» 29 Β· π 210 Β· π¦ 68 Β· π 440 - 32% open Β· β±οΈ 25.09.2024):
```
git clone https://github.com/tf-encrypted/tf-encrypted
```
- [PyPi](https://pypi.org/project/tf-encrypted) (π₯ 700 / month Β· π¦ 9 Β· β±οΈ 16.11.2022):
```
pip install tf-encrypted
```
</details>
<details><summary>Show 1 hidden projects...</summary>
- <b><a href="https://github.com/OpenMined/PipelineDP">PipelineDP</a></b> (π₯20 Β· β 280) - PipelineDP is a Python framework for applying differentially.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
</details>
<br>
## Workflow & Experiment Tracking
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries to organize, track, and visualize machine learning experiments._
<details><summary><b><a href="https://github.com/mlflow/mlflow">mlflow</a></b> (π₯44 Β· β 19K) - Open source platform for the machine learning lifecycle. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/mlflow/mlflow) (π¨βπ» 800 Β· π 4.3K Β· π¦ 48K Β· π 4.3K - 38% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/mlflow/mlflow
```
- [PyPi](https://pypi.org/project/mlflow) (π₯ 15M / month Β· π¦ 930 Β· β±οΈ 11.12.2024):
```
pip install mlflow
```
- [Conda](https://anaconda.org/conda-forge/mlflow) (π₯ 2.6M Β· β±οΈ 12.12.2024):
```
conda install -c conda-forge mlflow
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/tensorboard">Tensorboard</a></b> (π₯43 Β· β 6.7K) - TensorFlows Visualization Toolkit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/tensorboard) (π¨βπ» 320 Β· π 1.7K Β· π¦ 280K Β· π 1.9K - 35% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/tensorflow/tensorboard
```
- [PyPi](https://pypi.org/project/tensorboard) (π₯ 27M / month Β· π¦ 2.2K Β· β±οΈ 25.09.2024):
```
pip install tensorboard
```
- [Conda](https://anaconda.org/conda-forge/tensorboard) (π₯ 5.2M Β· β±οΈ 10.12.2024):
```
conda install -c conda-forge tensorboard
```
</details>
<details><summary><b><a href="https://github.com/wandb/wandb">wandb client</a></b> (π₯42 Β· β 9.3K) - The AI developer platform. Use Weights & Biases to train and fine-.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/wandb/wandb) (π¨βπ» 200 Β· π 680 Β· π₯ 410 Β· π¦ 61K Β· π 3.4K - 17% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/wandb/client
```
- [PyPi](https://pypi.org/project/wandb) (π₯ 18M / month Β· π¦ 1.6K Β· β±οΈ 13.12.2024):
```
pip install wandb
```
- [Conda](https://anaconda.org/conda-forge/wandb) (π₯ 800K Β· β±οΈ 14.12.2024):
```
conda install -c conda-forge wandb
```
</details>
<details><summary><b><a href="https://github.com/iterative/dvc">DVC</a></b> (π₯41 Β· β 14K) - Data Versioning and ML Experiments. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/iterative/dvc) (π¨βπ» 310 Β· π 1.2K Β· π¦ 20K Β· π 4.7K - 5% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/iterative/dvc
```
- [PyPi](https://pypi.org/project/dvc) (π₯ 530K / month Β· π¦ 130 Β· β±οΈ 01.12.2024):
```
pip install dvc
```
- [Conda](https://anaconda.org/conda-forge/dvc) (π₯ 2.4M Β· β±οΈ 01.12.2024):
```
conda install -c conda-forge dvc
```
</details>
<details><summary><b><a href="https://github.com/aws/sagemaker-python-sdk">SageMaker SDK</a></b> (π₯41 Β· β 2.1K) - A library for training and deploying machine learning.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/aws/sagemaker-python-sdk) (π¨βπ» 460 Β· π 1.1K Β· π¦ 5K Β· π 1.6K - 22% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/aws/sagemaker-python-sdk
```
- [PyPi](https://pypi.org/project/sagemaker) (π₯ 25M / month Β· π¦ 160 Β· β±οΈ 05.12.2024):
```
pip install sagemaker
```
- [Conda](https://anaconda.org/conda-forge/sagemaker-python-sdk) (π₯ 1.2M Β· β±οΈ 17.12.2024):
```
conda install -c conda-forge sagemaker-python-sdk
```
</details>
<details><summary><b><a href="https://github.com/Netflix/metaflow">Metaflow</a></b> (π₯36 Β· β 8.4K) - Open Source AI/ML Platform. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/Netflix/metaflow) (π¨βπ» 100 Β· π 770 Β· π¦ 770 Β· π 760 - 43% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/Netflix/metaflow
```
- [PyPi](https://pypi.org/project/metaflow) (π₯ 1.2M / month Β· π¦ 47 Β· β±οΈ 10.12.2024):
```
pip install metaflow
```
- [Conda](https://anaconda.org/conda-forge/metaflow) (π₯ 240K Β· β±οΈ 05.12.2024):
```
conda install -c conda-forge metaflow
```
</details>
<details><summary><b><a href="https://github.com/pycaret/pycaret">PyCaret</a></b> (π₯35 Β· β 9K) - An open-source, low-code machine learning library in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/pycaret/pycaret) (π¨βπ» 140 Β· π 1.8K Β· π₯ 720 Β· π¦ 6.8K Β· π 2.3K - 16% open Β· β±οΈ 30.08.2024):
```
git clone https://github.com/pycaret/pycaret
```
- [PyPi](https://pypi.org/project/pycaret) (π₯ 380K / month Β· π¦ 31 Β· β±οΈ 28.04.2024):
```
pip install pycaret
```
- [Conda](https://anaconda.org/conda-forge/pycaret) (π₯ 60K Β· β±οΈ 25.04.2024):
```
conda install -c conda-forge pycaret
```
</details>
<details><summary><b><a href="https://github.com/snakemake/snakemake">snakemake</a></b> (π₯34 Β· β 2.3K) - This is the development home of the workflow management system.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/snakemake/snakemake) (π¨βπ» 340 Β· π 560 Β· π¦ 2.2K Β· π 1.9K - 61% open Β· β±οΈ 11.12.2024):
```
git clone https://github.com/snakemake/snakemake
```
- [PyPi](https://pypi.org/project/snakemake) (π₯ 99K / month Β· π¦ 250 Β· β±οΈ 29.11.2024):
```
pip install snakemake
```
- [Conda](https://anaconda.org/bioconda/snakemake) (π₯ 1.3M Β· β±οΈ 02.12.2024):
```
conda install -c bioconda snakemake
```
</details>
<details><summary><b><a href="https://github.com/lanpa/tensorboardX">tensorboardX</a></b> (π₯33 Β· β 7.9K) - tensorboard for pytorch (and chainer, mxnet, numpy, ...). <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/lanpa/tensorboardX) (π¨βπ» 82 Β· π 860 Β· π₯ 460 Β· π¦ 52K Β· π 460 - 17% open Β· β±οΈ 16.11.2024):
```
git clone https://github.com/lanpa/tensorboardX
```
- [PyPi](https://pypi.org/project/tensorboardX) (π₯ 3.5M / month Β· π¦ 620 Β· β±οΈ 20.08.2023):
```
pip install tensorboardX
```
- [Conda](https://anaconda.org/conda-forge/tensorboardx) (π₯ 1.2M Β· β±οΈ 20.08.2023):
```
conda install -c conda-forge tensorboardx
```
</details>
<details><summary><b><a href="https://github.com/Kaggle/kaggle-api">kaggle</a></b> (π₯33 Β· β 6.3K) - Official Kaggle API. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/Kaggle/kaggle-api) (π¨βπ» 48 Β· π 1.1K Β· π¦ 21 Β· π 490 - 30% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/Kaggle/kaggle-api
```
- [PyPi](https://pypi.org/project/kaggle) (π₯ 260K / month Β· π¦ 210 Β· β±οΈ 24.07.2024):
```
pip install kaggle
```
- [Conda](https://anaconda.org/conda-forge/kaggle) (π₯ 200K Β· β±οΈ 27.07.2024):
```
conda install -c conda-forge kaggle
```
</details>
<details><summary><b><a href="https://github.com/allegroai/clearml">ClearML</a></b> (π₯33 Β· β 5.8K) - ClearML - Auto-Magical CI/CD to streamline your AI workload... <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/allegroai/clearml) (π¨βπ» 100 Β· π 660 Β· π₯ 3K Β· π¦ 1.4K Β· π 1.1K - 46% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/allegroai/clearml
```
- [PyPi](https://pypi.org/project/clearml) (π₯ 320K / month Β· π¦ 51 Β· β±οΈ 18.12.2024):
```
pip install clearml
```
- [Docker Hub](https://hub.docker.com/r/allegroai/trains) (π₯ 30K Β· β±οΈ 05.10.2020):
```
docker pull allegroai/trains
```
</details>
<details><summary><b><a href="https://github.com/aimhubio/aim">aim</a></b> (π₯32 Β· β 5.3K) - Aim An easy-to-use & supercharged open-source experiment tracker. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/aimhubio/aim) (π¨βπ» 78 Β· π 320 Β· π¦ 760 Β· π 1.1K - 36% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/aimhubio/aim
```
- [PyPi](https://pypi.org/project/aim) (π₯ 150K / month Β· π¦ 40 Β· β±οΈ 18.12.2024):
```
pip install aim
```
- [Conda](https://anaconda.org/conda-forge/aim) (π₯ 90K Β· β±οΈ 14.06.2024):
```
conda install -c conda-forge aim
```
</details>
<details><summary><b><a href="https://github.com/IDSIA/sacred">sacred</a></b> (π₯32 Β· β 4.3K) - Sacred is a tool to help you configure, organize, log and reproduce.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/IDSIA/sacred) (π¨βπ» 110 Β· π 380 Β· π¦ 3.3K Β· π 560 - 18% open Β· β±οΈ 26.11.2024):
```
git clone https://github.com/IDSIA/sacred
```
- [PyPi](https://pypi.org/project/sacred) (π₯ 280K / month Β· π¦ 60 Β· β±οΈ 26.11.2024):
```
pip install sacred
```
- [Conda](https://anaconda.org/conda-forge/sacred) (π₯ 7.4K Β· β±οΈ 28.11.2023):
```
conda install -c conda-forge sacred
```
</details>
<details><summary><b><a href="https://github.com/Azure/MachineLearningNotebooks">AzureML SDK</a></b> (π₯32 Β· β 4.1K) - Python notebooks with ML and deep learning examples with Azure.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/Azure/MachineLearningNotebooks) (π¨βπ» 64 Β· π 2.5K Β· π₯ 660 Β· π 1.5K - 26% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/Azure/MachineLearningNotebooks
```
- [PyPi](https://pypi.org/project/azureml-sdk) (π₯ 310K / month Β· π¦ 31 Β· β±οΈ 10.12.2024):
```
pip install azureml-sdk
```
</details>
<details><summary><b><a href="https://github.com/PaddlePaddle/VisualDL">VisualDL</a></b> (π₯30 Β· β 4.8K) - Deep Learning Visualization Toolkit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/PaddlePaddle/VisualDL) (π¨βπ» 36 Β· π 630 Β· π₯ 480 Β· π¦ 2 Β· π 500 - 28% open Β· β±οΈ 11.12.2024):
```
git clone https://github.com/PaddlePaddle/VisualDL
```
- [PyPi](https://pypi.org/project/visualdl) (π₯ 240K / month Β· π¦ 82 Β· β±οΈ 30.10.2024):
```
pip install visualdl
```
</details>
<details><summary><b><a href="https://github.com/neptune-ai/neptune-client">Neptune.ai</a></b> (π₯30 Β· β 590) - The experiment tracker for foundation model training. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/neptune-ai/neptune-client) (π¨βπ» 55 Β· π 64 Β· π¦ 700 Β· π 240 - 10% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/neptune-ai/neptune-client
```
- [PyPi](https://pypi.org/project/neptune-client) (π₯ 520K / month Β· π¦ 77 Β· β±οΈ 31.10.2024):
```
pip install neptune-client
```
- [Conda](https://anaconda.org/conda-forge/neptune-client) (π₯ 300K Β· β±οΈ 31.10.2024):
```
conda install -c conda-forge neptune-client
```
</details>
<details><summary><b><a href="https://github.com/labmlai/labml">Labml</a></b> (π₯28 Β· β 2.1K) - Monitor deep learning model training and hardware usage from your mobile.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/labmlai/labml) (π¨βπ» 9 Β· π 140 Β· π¦ 200 Β· π 48 - 10% open Β· β±οΈ 16.11.2024):
```
git clone https://github.com/labmlai/labml
```
- [PyPi](https://pypi.org/project/labml) (π₯ 5K / month Β· π¦ 14 Β· β±οΈ 15.09.2024):
```
pip install labml
```
</details>
<details><summary><b><a href="https://github.com/google/ml-metadata">ml-metadata</a></b> (π₯28 Β· β 630) - For recording and retrieving metadata associated with ML.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/google/ml-metadata) (π¨βπ» 21 Β· π 150 Β· π₯ 2.8K Β· π¦ 600 Β· π 120 - 38% open Β· β±οΈ 24.10.2024):
```
git clone https://github.com/google/ml-metadata
```
- [PyPi](https://pypi.org/project/ml-metadata) (π₯ 86K / month Β· π¦ 31 Β· β±οΈ 01.10.2024):
```
pip install ml-metadata
```
</details>
<details><summary><b><a href="https://github.com/pytorch/tnt">TNT</a></b> (π₯26 Β· β 1.7K) - A lightweight library for PyTorch training tools and utilities. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pytorch/tnt) (π¨βπ» 140 Β· π 280 Β· π 150 - 56% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/pytorch/tnt
```
- [PyPi](https://pypi.org/project/torchnet) (π₯ 4.9K / month Β· π¦ 24 Β· β±οΈ 29.07.2018):
```
pip install torchnet
```
</details>
<details><summary><b><a href="https://github.com/mrpowers-io/quinn">quinn</a></b> (π₯26 Β· β 650) - pyspark methods to enhance developer productivity. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/mrpowers-io/quinn) (π¨βπ» 31 Β· π 98 Β· π₯ 52 Β· π¦ 89 Β· π 130 - 27% open Β· β±οΈ 06.12.2024):
```
git clone https://github.com/MrPowers/quinn
```
- [PyPi](https://pypi.org/project/quinn) (π₯ 700K / month Β· π¦ 7 Β· β±οΈ 13.02.2024):
```
pip install quinn
```
</details>
<details><summary><b><a href="https://github.com/m3dev/gokart">gokart</a></b> (π₯25 Β· β 320) - Gokart solves reproducibility, task dependencies, constraints of good code,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/m3dev/gokart) (π¨βπ» 41 Β· π 58 Β· π¦ 84 Β· π 85 - 25% open Β· β±οΈ 10.12.2024):
```
git clone https://github.com/m3dev/gokart
```
- [PyPi](https://pypi.org/project/gokart) (π₯ 4.6K / month Β· π¦ 8 Β· β±οΈ 02.12.2024):
```
pip install gokart
```
</details>
<details><summary><b><a href="https://github.com/replicate/keepsake">keepsake</a></b> (π₯18 Β· β 1.6K) - Version control for machine learning. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/replicate/keepsake) (π¨βπ» 18 Β· π 71 Β· π 190 - 66% open Β· β±οΈ 03.12.2024):
```
git clone https://github.com/replicate/keepsake
```
- [PyPi](https://pypi.org/project/keepsake) (π₯ 170 / month Β· π¦ 1 Β· β±οΈ 25.01.2021):
```
pip install keepsake
```
</details>
<details><summary><b><a href="https://github.com/google/caliban">caliban</a></b> (π₯16 Β· β 500 Β· π€) - Research workflows made easy, locally and in the Cloud. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/google/caliban) (π¨βπ» 10 Β· π 66 Β· π¦ 4 Β· π 34 - 55% open Β· β±οΈ 25.01.2024):
```
git clone https://github.com/google/caliban
```
- [PyPi](https://pypi.org/project/caliban) (π₯ 440 / month Β· β±οΈ 12.09.2020):
```
pip install caliban
```
</details>
<details><summary><b><a href="https://www.comet.com">CometML</a></b> (π₯16) - Supercharging Machine Learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub]():
```
git clone https://github.com/comet-ml/examples
```
- [PyPi](https://pypi.org/project/comet_ml) (π₯ 450K / month Β· π¦ 83 Β· β±οΈ 16.12.2024):
```
pip install comet_ml
```
- [Conda](https://anaconda.org/anaconda/comet_ml):
```
conda install -c anaconda comet_ml
```
</details>
<details><summary>Show 16 hidden projects...</summary>
- <b><a href="https://github.com/catalyst-team/catalyst">Catalyst</a></b> (π₯28 Β· β 3.3K Β· π) - Accelerated deep learning R&D. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/huggingface/knockknock">knockknock</a></b> (π₯25 Β· β 2.8K Β· π) - Knock Knock: Get notified when your training ends with only two.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/stared/livelossplot">livelossplot</a></b> (π₯25 Β· β 1.3K Β· π) - Live training loss plot in Jupyter Notebook for Keras,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/EducationalTestingService/skll">SKLL</a></b> (π₯24 Β· β 550) - SciKit-Learn Laboratory (SKLL) makes it easy to run machine.. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">βοΈBSD-1-Clause</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/guildai/guildai">Guild AI</a></b> (π₯23 Β· β 870 Β· π) - Experiment tracking, ML developer tools. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/waleedka/hiddenlayer">hiddenlayer</a></b> (π₯22 Β· β 1.8K Β· π) - Neural network graphs and training metrics for.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/studioml/studio">Studio.ml</a></b> (π₯22 Β· β 380 Β· π) - Studio: Simplify and expedite model building process. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/instacart/lore">lore</a></b> (π₯21 Β· β 1.6K Β· π) - Lore makes machine learning approachable for Software Engineers and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/TeamHG-Memex/tensorboard_logger">TensorBoard Logger</a></b> (π₯21 Β· β 630 Β· π) - Log TensorBoard events without touching TensorFlow. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/microsoft/tensorwatch">TensorWatch</a></b> (π₯20 Β· β 3.4K Β· π) - Debugging, monitoring and visualization for Python Machine.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/awslabs/mxboard">MXBoard</a></b> (π₯20 Β· β 320 Β· π) - Logging MXNet data for visualization in TensorBoard. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/datmo/datmo">datmo</a></b> (π₯18 Β· β 340 Β· π) - Open source production model management tool for data scientists. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/aniketmaurya/chitra">chitra</a></b> (π₯17 Β· β 220) - A multi-functional library for full-stack Deep Learning. Simplifies.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/minerva-ml/steppy">steppy</a></b> (π₯16 Β· β 130 Β· π) - Lightweight, Python library for fast and reproducible experimentation. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/ModelChimp/modelchimp">ModelChimp</a></b> (π₯13 Β· β 130 Β· π) - Experiment tracking for machine and deep learning projects. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code>
- <b><a href="https://github.com/jrieke/traintool">traintool</a></b> (π₯9 Β· β 12 Β· π) - Train off-the-shelf machine learning models in one.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
</details>
<br>
## Model Serialization & Deployment
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries to serialize models to files, convert between a variety of model formats, and optimize models for deployment._
<details><summary><b><a href="https://github.com/onnx/onnx">onnx</a></b> (π₯43 Β· β 18K) - Open standard for machine learning interoperability. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/onnx/onnx) (π¨βπ» 330 Β· π 3.7K Β· π₯ 23K Β· π¦ 38K Β· π 2.9K - 12% open Β· β±οΈ 11.12.2024):
```
git clone https://github.com/onnx/onnx
```
- [PyPi](https://pypi.org/project/onnx) (π₯ 6.4M / month Β· π¦ 1.1K Β· β±οΈ 01.10.2024):
```
pip install onnx
```
- [Conda](https://anaconda.org/conda-forge/onnx) (π₯ 1.4M Β· β±οΈ 21.10.2024):
```
conda install -c conda-forge onnx
```
</details>
<details><summary><b><a href="https://github.com/triton-lang/triton">triton</a></b> (π₯43 Β· β 14K) - Development repository for the Triton language and compiler. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/triton-lang/triton) (π¨βπ» 350 Β· π 1.7K Β· π¦ 47K Β· π 1.6K - 43% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/openai/triton
```
- [PyPi](https://pypi.org/project/triton) (π₯ 16M / month Β· π¦ 260 Β· β±οΈ 14.10.2024):
```
pip install triton
```
</details>
<details><summary><b><a href="https://github.com/huggingface/huggingface_hub">huggingface_hub</a></b> (π₯38 Β· β 2.2K) - The official Python client for the Huggingface Hub. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/huggingface/huggingface_hub) (π¨βπ» 210 Β· π 570 Β· π 1K - 15% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/huggingface/huggingface_hub
```
- [PyPi](https://pypi.org/project/huggingface_hub) (π₯ 54M / month Β· π¦ 2.2K Β· β±οΈ 16.12.2024):
```
pip install huggingface_hub
```
- [Conda](https://anaconda.org/conda-forge/huggingface_hub) (π₯ 2.5M Β· β±οΈ 10.12.2024):
```
conda install -c conda-forge huggingface_hub
```
</details>
<details><summary><b><a href="https://github.com/apple/coremltools">Core ML Tools</a></b> (π₯36 Β· β 4.5K) - Core ML tools contain supporting tools for Core ML model.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/apple/coremltools) (π¨βπ» 180 Β· π 640 Β· π₯ 12K Β· π¦ 4.3K Β· π 1.5K - 24% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/apple/coremltools
```
- [PyPi](https://pypi.org/project/coremltools) (π₯ 750K / month Β· π¦ 87 Β· β±οΈ 20.11.2024):
```
pip install coremltools
```
- [Conda](https://anaconda.org/conda-forge/coremltools) (π₯ 77K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge coremltools
```
</details>
<details><summary><b><a href="https://github.com/bentoml/BentoML">BentoML</a></b> (π₯35 Β· β 7.2K) - The easiest way to serve AI apps and models - Build Model Inference.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/bentoml/BentoML) (π¨βπ» 210 Β· π 800 Β· π₯ 850 Β· π¦ 2.3K Β· π 1.1K - 15% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/bentoml/BentoML
```
- [PyPi](https://pypi.org/project/bentoml) (π₯ 110K / month Β· π¦ 31 Β· β±οΈ 12.12.2024):
```
pip install bentoml
```
</details>
<details><summary><b><a href="https://github.com/pytorch/serve">TorchServe</a></b> (π₯34 Β· β 4.3K) - Serve, optimize and scale PyTorch models in production. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pytorch/serve) (π¨βπ» 220 Β· π 870 Β· π₯ 7.3K Β· π¦ 780 Β· π 1.7K - 25% open Β· β±οΈ 05.12.2024):
```
git clone https://github.com/pytorch/serve
```
- [PyPi](https://pypi.org/project/torchserve) (π₯ 55K / month Β· π¦ 22 Β· β±οΈ 30.09.2024):
```
pip install torchserve
```
- [Conda](https://anaconda.org/pytorch/torchserve) (π₯ 390K Β· β±οΈ 30.09.2024):
```
conda install -c pytorch torchserve
```
- [Docker Hub](https://hub.docker.com/r/pytorch/torchserve) (π₯ 1.4M Β· β 30 Β· β±οΈ 30.09.2024):
```
docker pull pytorch/torchserve
```
</details>
<details><summary><b><a href="https://github.com/fastmachinelearning/hls4ml">hls4ml</a></b> (π₯27 Β· β 1.3K) - Machine learning on FPGAs using HLS. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/fastmachinelearning/hls4ml) (π¨βπ» 63 Β· π 420 Β· π 460 - 41% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/fastmachinelearning/hls4ml
```
- [PyPi](https://pypi.org/project/hls4ml) (π₯ 1.2K / month Β· π¦ 1 Β· β±οΈ 09.12.2024):
```
pip install hls4ml
```
- [Conda](https://anaconda.org/conda-forge/hls4ml) (π₯ 9.3K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge hls4ml
```
</details>
<details><summary><b><a href="https://github.com/microsoft/hummingbird">Hummingbird</a></b> (π₯25 Β· β 3.4K) - Hummingbird compiles trained ML models into tensor computation for.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/microsoft/hummingbird) (π¨βπ» 40 Β· π 280 Β· π₯ 770 Β· π 330 - 20% open Β· β±οΈ 24.10.2024):
```
git clone https://github.com/microsoft/hummingbird
```
- [PyPi](https://pypi.org/project/hummingbird-ml) (π₯ 7.6K / month Β· π¦ 7 Β· β±οΈ 25.10.2024):
```
pip install hummingbird-ml
```
- [Conda](https://anaconda.org/conda-forge/hummingbird-ml):
```
conda install -c conda-forge hummingbird-ml
```
</details>
<details><summary><b><a href="https://github.com/nebuly-ai/optimate">nebullvm</a></b> (π₯21 Β· β 8.4K) - A collection of libraries to optimise AI model performances. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/nebuly-ai/optimate) (π¨βπ» 40 Β· π 630 Β· π 200 - 49% open Β· β±οΈ 22.07.2024):
```
git clone https://github.com/nebuly-ai/nebullvm
```
- [PyPi](https://pypi.org/project/nebullvm) (π₯ 680 / month Β· π¦ 2 Β· β±οΈ 18.06.2023):
```
pip install nebullvm
```
</details>
<details><summary><b><a href="https://github.com/riga/tfdeploy">tfdeploy</a></b> (π₯17 Β· β 350 Β· π€) - Deploy tensorflow graphs for fast evaluation and export to.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/riga/tfdeploy) (π¨βπ» 4 Β· π 38 Β· π 34 - 32% open Β· β±οΈ 25.02.2024):
```
git clone https://github.com/riga/tfdeploy
```
- [PyPi](https://pypi.org/project/tfdeploy) (π₯ 180 / month Β· β±οΈ 30.03.2017):
```
pip install tfdeploy
```
</details>
<details><summary>Show 10 hidden projects...</summary>
- <b><a href="https://github.com/microsoft/MMdnn">mmdnn</a></b> (π₯25 Β· β 5.8K Β· π) - MMdnn is a set of tools to help users inter-operate among different deep.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/BayesWitnesses/m2cgen">m2cgen</a></b> (π₯25 Β· β 2.8K Β· π) - Transform ML models into a native code (Java, C, Python, Go,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/cortexlabs/cortex">cortex</a></b> (π₯23 Β· β 8K Β· π) - Production infrastructure for machine learning at scale. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/nok/sklearn-porter">sklearn-porter</a></b> (π₯23 Β· β 1.3K Β· π) - Transpile trained scikit-learn estimators to C, Java,.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/cog-imperial/OMLT">OMLT</a></b> (π₯20 Β· β 290) - Represent trained machine learning models as Pyomo optimization.. <code>βUnlicensed</code>
- <b><a href="https://github.com/larq/compute-engine">Larq Compute Engine</a></b> (π₯20 Β· β 240) - Highly optimized inference engine for Binarized.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/gmalivenko/pytorch2keras">pytorch2keras</a></b> (π₯19 Β· β 860 Β· π) - PyTorch to Keras model convertor. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/Cornerstone-OnDemand/modelkit">modelkit</a></b> (π₯17 Β· β 150) - Toolkit for developing and maintaining ML models. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/backprop-ai/backprop">backprop</a></b> (π₯15 Β· β 240 Β· π) - Backprop makes it simple to use, finetune, and deploy state-of-.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/apple/ml-ane-transformers">ml-ane-transformers</a></b> (π₯13 Β· β 2.6K Β· π) - Reference implementation of the Transformer.. <code>βUnlicensed</code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
</details>
<br>
## Model Interpretability
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries to visualize, explain, debug, evaluate, and interpret machine learning models._
<details><summary><b><a href="https://github.com/shap/shap">shap</a></b> (π₯41 Β· β 23K) - A game theoretic approach to explain the output of any machine learning model. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/shap/shap) (π¨βπ» 250 Β· π 3.3K Β· π¦ 23K Β· π 2.6K - 27% open Β· β±οΈ 13.12.2024):
```
git clone https://github.com/slundberg/shap
```
- [PyPi](https://pypi.org/project/shap) (π₯ 7M / month Β· π¦ 750 Β· β±οΈ 27.06.2024):
```
pip install shap
```
- [Conda](https://anaconda.org/conda-forge/shap) (π₯ 4.6M Β· β±οΈ 10.12.2024):
```
conda install -c conda-forge shap
```
</details>
<details><summary><b><a href="https://github.com/lutzroeder/netron">Netron</a></b> (π₯37 Β· β 29K) - Visualizer for neural network, deep learning and machine learning.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/lutzroeder/netron) (π¨βπ» 2 Β· π 2.8K Β· π₯ 130K Β· π¦ 610 Β· π 1.2K - 1% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/lutzroeder/netron
```
- [PyPi](https://pypi.org/project/netron) (π₯ 32K / month Β· π¦ 83 Β· β±οΈ 14.12.2024):
```
pip install netron
```
</details>
<details><summary><b><a href="https://github.com/arviz-devs/arviz">arviz</a></b> (π₯35 Β· β 1.6K) - Exploratory analysis of Bayesian models with Python. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/arviz-devs/arviz) (π¨βπ» 160 Β· π 410 Β· π₯ 180 Β· π¦ 8.6K Β· π 870 - 20% open Β· β±οΈ 19.11.2024):
```
git clone https://github.com/arviz-devs/arviz
```
- [PyPi](https://pypi.org/project/arviz) (π₯ 1.3M / month Β· π¦ 310 Β· β±οΈ 28.09.2024):
```
pip install arviz
```
- [Conda](https://anaconda.org/conda-forge/arviz) (π₯ 2.3M Β· β±οΈ 13.12.2024):
```
conda install -c conda-forge arviz
```
</details>
<details><summary><b><a href="https://github.com/interpretml/interpret">InterpretML</a></b> (π₯34 Β· β 6.3K) - Fit interpretable models. Explain blackbox machine learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/interpretml/interpret) (π¨βπ» 48 Β· π 740 Β· π¦ 810 Β· π 460 - 23% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/interpretml/interpret
```
- [PyPi](https://pypi.org/project/interpret) (π₯ 140K / month Β· π¦ 50 Β· β±οΈ 10.12.2024):
```
pip install interpret
```
</details>
<details><summary><b><a href="https://github.com/pytorch/captum">Captum</a></b> (π₯34 Β· β 5K) - Model interpretability and understanding for PyTorch. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pytorch/captum) (π¨βπ» 120 Β· π 500 Β· π¦ 2.6K Β· π 590 - 42% open Β· β±οΈ 12.12.2024):
```
git clone https://github.com/pytorch/captum
```
- [PyPi](https://pypi.org/project/captum) (π₯ 290K / month Β· π¦ 130 Β· β±οΈ 05.12.2023):
```
pip install captum
```
- [Conda](https://anaconda.org/conda-forge/captum) (π₯ 110K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge captum
```
</details>
<details><summary><b><a href="https://github.com/MAIF/shapash">shapash</a></b> (π₯31 Β· β 2.8K) - Shapash: User-friendly Explainability and Interpretability to.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/MAIF/shapash) (π¨βπ» 40 Β· π 340 Β· π¦ 180 Β· π 220 - 17% open Β· β±οΈ 09.12.2024):
```
git clone https://github.com/MAIF/shapash
```
- [PyPi](https://pypi.org/project/shapash) (π₯ 24K / month Β· π¦ 4 Β· β±οΈ 09.12.2024):
```
pip install shapash
```
</details>
<details><summary><b><a href="https://github.com/huggingface/evaluate">evaluate</a></b> (π₯31 Β· β 2.1K) - Evaluate: A library for easily evaluating machine learning models.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/huggingface/evaluate) (π¨βπ» 130 Β· π 260 Β· π¦ 16K Β· π 360 - 60% open Β· β±οΈ 17.09.2024):
```
git clone https://github.com/huggingface/evaluate
```
- [PyPi](https://pypi.org/project/evaluate) (π₯ 2.7M / month Β· π¦ 400 Β· β±οΈ 11.09.2024):
```
pip install evaluate
```
</details>
<details><summary><b><a href="https://github.com/fairlearn/fairlearn">fairlearn</a></b> (π₯30 Β· β 2K) - A Python package to assess and improve fairness of machine learning.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/fairlearn/fairlearn) (π¨βπ» 91 Β· π 420 Β· π¦ 3 Β· π 490 - 32% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/fairlearn/fairlearn
```
- [PyPi](https://pypi.org/project/fairlearn) (π₯ 190K / month Β· π¦ 63 Β· β±οΈ 11.12.2024):
```
pip install fairlearn
```
- [Conda](https://anaconda.org/conda-forge/fairlearn) (π₯ 39K Β· β±οΈ 13.12.2024):
```
conda install -c conda-forge fairlearn
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/model-analysis">Model Analysis</a></b> (π₯30 Β· β 1.3K) - Model analysis tools for TensorFlow. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/model-analysis) (π¨βπ» 59 Β· π 280 Β· π 93 - 40% open Β· β±οΈ 27.11.2024):
```
git clone https://github.com/tensorflow/model-analysis
```
- [PyPi](https://pypi.org/project/tensorflow-model-analysis) (π₯ 260K / month Β· π¦ 19 Β· β±οΈ 05.12.2024):
```
pip install tensorflow-model-analysis
```
</details>
<details><summary><b><a href="https://github.com/py-why/dowhy">DoWhy</a></b> (π₯29 Β· β 7.2K) - DoWhy is a Python library for causal inference that supports explicit.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/py-why/dowhy) (π¨βπ» 99 Β· π 940 Β· π₯ 42 Β· π¦ 470 Β· π 480 - 27% open Β· β±οΈ 24.11.2024):
```
git clone https://github.com/py-why/dowhy
```
- [PyPi](https://pypi.org/project/dowhy) (π₯ 55K / month Β· π¦ 18 Β· β±οΈ 24.11.2024):
```
pip install dowhy
```
- [Conda](https://anaconda.org/conda-forge/dowhy) (π₯ 36K Β· β±οΈ 25.11.2024):
```
conda install -c conda-forge dowhy
```
</details>
<details><summary><b><a href="https://github.com/PAIR-code/lit">LIT</a></b> (π₯29 Β· β 3.5K) - The Learning Interpretability Tool: Interactively analyze ML models to.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/PAIR-code/lit) (π¨βπ» 38 Β· π 360 Β· π¦ 42 Β· π 200 - 57% open Β· β±οΈ 22.10.2024):
```
git clone https://github.com/PAIR-code/lit
```
- [PyPi](https://pypi.org/project/lit-nlp) (π₯ 7.3K / month Β· π¦ 3 Β· β±οΈ 22.10.2024):
```
pip install lit-nlp
```
- [Conda](https://anaconda.org/conda-forge/lit-nlp) (π₯ 99K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge lit-nlp
```
</details>
<details><summary><b><a href="https://github.com/oegedijk/explainerdashboard">explainerdashboard</a></b> (π₯29 Β· β 2.3K) - Quickly build Explainable AI dashboards that show the inner.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/oegedijk/explainerdashboard) (π¨βπ» 21 Β· π 330 Β· π¦ 580 Β· π 240 - 14% open Β· β±οΈ 20.06.2024):
```
git clone https://github.com/oegedijk/explainerdashboard
```
- [PyPi](https://pypi.org/project/explainerdashboard) (π₯ 64K / month Β· π¦ 10 Β· β±οΈ 18.03.2024):
```
pip install explainerdashboard
```
- [Conda](https://anaconda.org/conda-forge/explainerdashboard) (π₯ 57K Β· β±οΈ 18.03.2024):
```
conda install -c conda-forge explainerdashboard
```
</details>
<details><summary><b><a href="https://github.com/bmabey/pyLDAvis">pyLDAvis</a></b> (π₯29 Β· β 1.8K Β· π€) - Python library for interactive topic model visualization... <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/bmabey/pyLDAvis) (π¨βπ» 42 Β· π 360 Β· π¦ 6.7K Β· π 190 - 40% open Β· β±οΈ 29.04.2024):
```
git clone https://github.com/bmabey/pyLDAvis
```
- [PyPi](https://pypi.org/project/pyldavis) (π₯ 140K / month Β· π¦ 100 Β· β±οΈ 23.04.2023):
```
pip install pyldavis
```
- [Conda](https://anaconda.org/conda-forge/pyldavis) (π₯ 89K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge pyldavis
```
</details>
<details><summary><b><a href="https://github.com/parrt/dtreeviz">dtreeviz</a></b> (π₯28 Β· β 3K) - A python library for decision tree visualization and model interpretation. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/parrt/dtreeviz) (π¨βπ» 27 Β· π 340 Β· π¦ 1.4K Β· π 210 - 34% open Β· β±οΈ 29.08.2024):
```
git clone https://github.com/parrt/dtreeviz
```
- [PyPi](https://pypi.org/project/dtreeviz) (π₯ 120K / month Β· π¦ 53 Β· β±οΈ 07.07.2022):
```
pip install dtreeviz
```
- [Conda](https://anaconda.org/conda-forge/dtreeviz) (π₯ 91K Β· β±οΈ 13.07.2023):
```
conda install -c conda-forge dtreeviz
```
</details>
<details><summary><b><a href="https://github.com/csinva/imodels">imodels</a></b> (π₯28 Β· β 1.4K) - Interpretable ML package for concise, transparent, and accurate.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/csinva/imodels) (π¨βπ» 24 Β· π 120 Β· π¦ 110 Β· π 94 - 39% open Β· β±οΈ 06.11.2024):
```
git clone https://github.com/csinva/imodels
```
- [PyPi](https://pypi.org/project/imodels) (π₯ 120K / month Β· π¦ 9 Β· β±οΈ 15.10.2024):
```
pip install imodels
```
</details>
<details><summary><b><a href="https://github.com/Trusted-AI/AIF360">Fairness 360</a></b> (π₯26 Β· β 2.5K) - A comprehensive set of fairness metrics for datasets and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/Trusted-AI/AIF360) (π¨βπ» 73 Β· π 840 Β· π¦ 540 Β· π 300 - 66% open Β· β±οΈ 10.12.2024):
```
git clone https://github.com/Trusted-AI/AIF360
```
- [PyPi](https://pypi.org/project/aif360) (π₯ 30K / month Β· π¦ 32 Β· β±οΈ 08.04.2024):
```
pip install aif360
```
- [Conda](https://anaconda.org/conda-forge/aif360) (π₯ 17K Β· β±οΈ 09.04.2024):
```
conda install -c conda-forge aif360
```
</details>
<details><summary><b><a href="https://github.com/microsoft/responsible-ai-toolbox">responsible-ai-widgets</a></b> (π₯26 Β· β 1.4K) - Responsible AI Toolbox is a suite of tools providing.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/microsoft/responsible-ai-toolbox) (π¨βπ» 43 Β· π 360 Β· π 320 - 26% open Β· β±οΈ 07.08.2024):
```
git clone https://github.com/microsoft/responsible-ai-toolbox
```
- [PyPi](https://pypi.org/project/raiwidgets) (π₯ 8.1K / month Β· π¦ 6 Β· β±οΈ 08.07.2024):
```
pip install raiwidgets
```
</details>
<details><summary><b><a href="https://github.com/mckinsey/causalnex">CausalNex</a></b> (π₯24 Β· β 2.3K Β· π€) - A Python library that helps data scientists to infer.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/mckinsey/causalnex) (π¨βπ» 40 Β· π 260 Β· π¦ 140 Β· π 140 - 17% open Β· β±οΈ 10.02.2024):
```
git clone https://github.com/quantumblacklabs/causalnex
```
- [PyPi](https://pypi.org/project/causalnex) (π₯ 2.9K / month Β· π¦ 4 Β· β±οΈ 22.06.2023):
```
pip install causalnex
```
</details>
<details><summary><b><a href="https://github.com/Trusted-AI/AIX360">Explainability 360</a></b> (π₯24 Β· β 1.6K) - Interpretability and explainability of data and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/Trusted-AI/AIX360) (π¨βπ» 41 Β· π 300 Β· π¦ 110 Β· π 85 - 63% open Β· β±οΈ 16.07.2024):
```
git clone https://github.com/Trusted-AI/AIX360
```
- [PyPi](https://pypi.org/project/aix360) (π₯ 1.1K / month Β· π¦ 1 Β· β±οΈ 31.07.2023):
```
pip install aix360
```
</details>
<details><summary><b><a href="https://github.com/dssg/aequitas">aequitas</a></b> (π₯23 Β· β 700) - Bias Auditing & Fair ML Toolkit. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/dssg/aequitas) (π¨βπ» 22 Β· π 120 Β· π¦ 180 Β· π 99 - 51% open Β· β±οΈ 11.09.2024):
```
git clone https://github.com/dssg/aequitas
```
- [PyPi](https://pypi.org/project/aequitas) (π₯ 26K / month Β· π¦ 8 Β· β±οΈ 30.01.2024):
```
pip install aequitas
```
</details>
<details><summary><b><a href="https://github.com/PAIR-code/what-if-tool">What-If Tool</a></b> (π₯22 Β· β 930 Β· π€) - Source code/webpage/demos for the What-If Tool. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/PAIR-code/what-if-tool) (π¨βπ» 20 Β· π 170 Β· π¦ 2 Β· π 150 - 61% open Β· β±οΈ 01.02.2024):
```
git clone https://github.com/PAIR-code/what-if-tool
```
- [PyPi](https://pypi.org/project/witwidget) (π₯ 6.3K / month Β· π¦ 6 Β· β±οΈ 12.10.2021):
```
pip install witwidget
```
- [Conda](https://anaconda.org/conda-forge/tensorboard-plugin-wit) (π₯ 2.3M Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge tensorboard-plugin-wit
```
- [npm](https://www.npmjs.com/package/wit-widget) (π₯ 520 / month Β· π¦ 3 Β· β±οΈ 12.10.2021):
```
npm install wit-widget
```
</details>
<details><summary><b><a href="https://github.com/jalammar/ecco">ecco</a></b> (π₯21 Β· β 2K) - Explain, analyze, and visualize NLP language models. Ecco creates.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/jalammar/ecco) (π¨βπ» 12 Β· π 160 Β· π₯ 130 Β· π¦ 32 Β· π 64 - 51% open Β· β±οΈ 15.08.2024):
```
git clone https://github.com/jalammar/ecco
```
- [PyPi](https://pypi.org/project/ecco) (π₯ 640 / month Β· π¦ 1 Β· β±οΈ 09.01.2022):
```
pip install ecco
```
- [Conda](https://anaconda.org/conda-forge/ecco) (π₯ 5.9K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge ecco
```
</details>
<details><summary><b><a href="https://github.com/interpretml/DiCE">DiCE</a></b> (π₯21 Β· β 1.4K) - Generate Diverse Counterfactual Explanations for any machine.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/interpretml/DiCE) (π¨βπ» 19 Β· π 190 Β· π 180 - 48% open Β· β±οΈ 22.11.2024):
```
git clone https://github.com/interpretml/DiCE
```
- [PyPi](https://pypi.org/project/dice-ml) (π₯ 35K / month Β· π¦ 6 Β· β±οΈ 27.10.2023):
```
pip install dice-ml
```
</details>
<details><summary><b><a href="https://github.com/parrt/random-forest-importances">random-forest-importances</a></b> (π₯21 Β· β 600) - Code to compute permutation and drop-column.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/parrt/random-forest-importances) (π¨βπ» 15 Β· π 130 Β· π¦ 170 Β· π 39 - 20% open Β· β±οΈ 29.09.2024):
```
git clone https://github.com/parrt/random-forest-importances
```
- [PyPi](https://pypi.org/project/rfpimp) (π₯ 13K / month Β· π¦ 5 Β· β±οΈ 28.01.2021):
```
pip install rfpimp
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/fairness-indicators">fairness-indicators</a></b> (π₯19 Β· β 340) - Tensorflows Fairness Evaluation and Visualization.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/fairness-indicators) (π¨βπ» 36 Β· π 79 Β· π 36 - 72% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/tensorflow/fairness-indicators
```
- [PyPi](https://pypi.org/project/fairness-indicators) (π₯ 1.7K / month Β· β±οΈ 26.04.2024):
```
pip install fairness-indicators
```
</details>
<details><summary><b><a href="https://github.com/aerdem4/lofo-importance">LOFO</a></b> (π₯18 Β· β 820 Β· π€) - Leave One Feature Out Importance. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/aerdem4/lofo-importance) (π¨βπ» 6 Β· π 85 Β· π¦ 35 Β· π 28 - 10% open Β· β±οΈ 16.01.2024):
```
git clone https://github.com/aerdem4/lofo-importance
```
- [PyPi](https://pypi.org/project/lofo-importance) (π₯ 4K / month Β· π¦ 4 Β· β±οΈ 16.01.2024):
```
pip install lofo-importance
```
</details>
<details><summary><b><a href="https://github.com/explainX/explainx">ExplainX.ai</a></b> (π₯15 Β· β 420) - Explainable AI framework for data scientists. Explain & debug any.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/explainX/explainx) (π¨βπ» 5 Β· π 53 Β· π₯ 20 Β· π 39 - 25% open Β· β±οΈ 21.08.2024):
```
git clone https://github.com/explainX/explainx
```
- [PyPi](https://pypi.org/project/explainx) (π₯ 800 / month Β· β±οΈ 04.02.2021):
```
pip install explainx
```
</details>
<details><summary><b><a href="https://github.com/interpretml/interpret-text">interpret-text</a></b> (π₯15 Β· β 420 Β· π€) - A library that incorporates state-of-the-art explainers.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/interpretml/interpret-text) (π¨βπ» 18 Β· π 69 Β· π 100 - 84% open Β· β±οΈ 05.02.2024):
```
git clone https://github.com/interpretml/interpret-text
```
- [PyPi](https://pypi.org/project/interpret-text) (π₯ 200 / month Β· β±οΈ 07.12.2021):
```
pip install interpret-text
```
</details>
<details><summary>Show 26 hidden projects...</summary>
- <b><a href="https://github.com/marcotcr/lime">Lime</a></b> (π₯32 Β· β 12K Β· π) - Lime: Explaining the predictions of any machine learning classifier. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code>
- <b><a href="https://github.com/deepchecks/deepchecks">Deep Checks</a></b> (π₯29 Β· β 3.7K) - Deepchecks: Tests for Continuous Validation of ML Models &.. <code><a href="http://bit.ly/3pwmjO5">βοΈAGPL-3.0</a></code>
- <b><a href="https://github.com/reiinakano/scikit-plot">scikit-plot</a></b> (π₯28 Β· β 2.4K Β· π) - An intuitive library to add plotting functionality to.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/ModelOriented/DALEX">DALEX</a></b> (π₯28 Β· β 1.4K) - moDel Agnostic Language for Exploration and eXplanation. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/DistrictDataLabs/yellowbrick">yellowbrick</a></b> (π₯27 Β· β 4.3K Β· π) - Visual analysis and diagnostic tools to facilitate.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/SeldonIO/alibi">Alibi</a></b> (π₯27 Β· β 2.4K) - Algorithms for explaining machine learning models. <code><a href="https://tldrlegal.com/search?q=Intel">βοΈIntel</a></code>
- <b><a href="https://github.com/TeamHG-Memex/eli5">eli5</a></b> (π₯26 Β· β 2.8K Β· π) - A library for debugging/inspecting machine learning classifiers and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/tensorflow/lucid">Lucid</a></b> (π₯25 Β· β 4.7K Β· π) - A collection of infrastructure and tools for research in.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/raghakot/keras-vis">keras-vis</a></b> (π₯25 Β· β 3K Β· π) - Neural network visualization toolkit for keras. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/albermax/innvestigate">iNNvestigate</a></b> (π₯25 Β· β 1.3K Β· π) - A toolbox to iNNvestigate neural networks predictions!. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/marcotcr/checklist">checklist</a></b> (π₯24 Β· β 2K Β· π) - Beyond Accuracy: Behavioral Testing of NLP models with CheckList. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/philipperemy/keract">keract</a></b> (π₯23 Β· β 1K Β· π) - Layers Outputs and Gradients in Keras. Made easy. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/sicara/tf-explain">tf-explain</a></b> (π₯22 Β· β 1K Β· π) - Interpretability Methods for tf.keras models with Tensorflow.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/kundajelab/deeplift">deeplift</a></b> (π₯21 Β· β 840 Β· π) - Public facing deeplift repo. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/andosa/treeinterpreter">TreeInterpreter</a></b> (π₯21 Β· β 740 Β· π) - Package for interpreting scikit-learns decision tree.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/understandable-machine-intelligence-lab/Quantus">Quantus</a></b> (π₯21 Β· β 570) - Quantus is an eXplainable AI toolkit for responsible evaluation of.. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/tensorflow/tcav">tcav</a></b> (π₯20 Β· β 630 Β· π) - Code for the TCAV ML interpretability project. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/EthicalML/xai">XAI</a></b> (π₯19 Β· β 1.1K Β· π) - XAI - An eXplainability toolbox for machine learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/edublancas/sklearn-evaluation">sklearn-evaluation</a></b> (π₯18 Β· β 460 Β· π) - Machine learning model evaluation made easy: plots,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/tensorflow/model-card-toolkit">model-card-toolkit</a></b> (π₯18 Β· β 430 Β· π) - A toolkit that streamlines and automates the.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/marcotcr/anchor">Anchor</a></b> (π₯16 Β· β 800 Β· π) - Code for High-Precision Model-Agnostic Explanations paper. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code>
- <b><a href="https://github.com/MisaOgura/flashtorch">FlashTorch</a></b> (π₯16 Β· β 740 Β· π) - Visualization toolkit for neural networks in PyTorch! Demo --. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/oracle/Skater">Skater</a></b> (π₯14 Β· β 1.1K Β· π) - Python Library for Model Interpretation/Explanations. <code><a href="https://tldrlegal.com/search?q=UPL-1.0">βοΈUPL-1.0</a></code>
- <b><a href="https://github.com/suinleelab/attributionpriors">Attribution Priors</a></b> (π₯13 Β· β 120 Β· π) - Tools for training explainable models using.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/intuit/bias-detector">bias-detector</a></b> (π₯13 Β· β 44 Β· π€) - Bias Detector is a python package for detecting bias in machine.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/SAP-archive/contextual-ai">contextual-ai</a></b> (π₯12 Β· β 86 Β· π) - Contextual AI adds explainability to different stages of.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
</details>
<br>
## Vector Similarity Search (ANN)
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for Approximate Nearest Neighbor Search and Vector Indexing/Similarity Search._
π <b><a href="https://github.com/erikbern/ann-benchmarks">ANN Benchmarks</a></b> ( β 5K) - Benchmarks of approximate nearest neighbor libraries in Python.
<details><summary><b><a href="https://github.com/facebookresearch/faiss">Faiss</a></b> (π₯41 Β· β 32K) - A library for efficient similarity search and clustering of dense vectors. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/facebookresearch/faiss) (π¨βπ» 200 Β· π 3.6K Β· π¦ 4.3K Β· π 2.6K - 9% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/facebookresearch/faiss
```
- [PyPi](https://pypi.org/project/pymilvus) (π₯ 1.4M / month Β· π¦ 190 Β· β±οΈ 26.11.2024):
```
pip install pymilvus
```
- [Conda](https://anaconda.org/conda-forge/faiss) (π₯ 2M Β· β±οΈ 09.08.2024):
```
conda install -c conda-forge faiss
```
</details>
<details><summary><b><a href="https://github.com/milvus-io/milvus">Milvus</a></b> (π₯41 Β· β 31K) - A cloud-native vector database, storage for next generation AI.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/milvus-io/milvus) (π¨βπ» 300 Β· π 3K Β· π₯ 290K Β· π 12K - 6% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/milvus-io/milvus
```
- [PyPi](https://pypi.org/project/pymilvus) (π₯ 1.4M / month Β· π¦ 190 Β· β±οΈ 26.11.2024):
```
pip install pymilvus
```
- [Docker Hub](https://hub.docker.com/r/milvusdb/milvus) (π₯ 67M Β· β 66 Β· β±οΈ 19.12.2024):
```
docker pull milvusdb/milvus
```
</details>
<details><summary><b><a href="https://github.com/spotify/annoy">Annoy</a></b> (π₯34 Β· β 13K) - Approximate Nearest Neighbors in C++/Python optimized for memory usage.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/spotify/annoy) (π¨βπ» 88 Β· π 1.2K Β· π¦ 4.6K Β· π 400 - 14% open Β· β±οΈ 29.07.2024):
```
git clone https://github.com/spotify/annoy
```
- [PyPi](https://pypi.org/project/annoy) (π₯ 860K / month Β· π¦ 200 Β· β±οΈ 14.06.2023):
```
pip install annoy
```
- [Conda](https://anaconda.org/conda-forge/python-annoy) (π₯ 590K Β· β±οΈ 05.09.2024):
```
conda install -c conda-forge python-annoy
```
</details>
<details><summary><b><a href="https://github.com/nmslib/hnswlib">hnswlib</a></b> (π₯32 Β· β 4.4K) - Header-only C++/python library for fast approximate nearest neighbors. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/nmslib/hnswlib) (π¨βπ» 72 Β· π 660 Β· π¦ 7.3K Β· π 410 - 59% open Β· β±οΈ 17.06.2024):
```
git clone https://github.com/nmslib/hnswlib
```
- [PyPi](https://pypi.org/project/hnswlib) (π₯ 730K / month Β· π¦ 130 Β· β±οΈ 03.12.2023):
```
pip install hnswlib
```
- [Conda](https://anaconda.org/conda-forge/hnswlib) (π₯ 270K Β· β±οΈ 20.11.2024):
```
conda install -c conda-forge hnswlib
```
</details>
<details><summary><b><a href="https://github.com/unum-cloud/usearch">USearch</a></b> (π₯31 Β· β 2.3K) - Fast Open-Source Search & Clustering engine for Vectors & Strings in.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/unum-cloud/usearch) (π¨βπ» 58 Β· π 150 Β· π₯ 39K Β· π¦ 140 Β· π 180 - 36% open Β· β±οΈ 13.12.2024):
```
git clone https://github.com/unum-cloud/usearch
```
- [PyPi](https://pypi.org/project/usearch) (π₯ 300K / month Β· π¦ 23 Β· β±οΈ 21.11.2024):
```
pip install usearch
```
- [npm](https://www.npmjs.com/package/usearch) (π₯ 6.7K / month Β· π¦ 15 Β· β±οΈ 13.12.2024):
```
npm install usearch
```
- [Docker Hub](https://hub.docker.com/r/unum/usearch) (π₯ 170 Β· β 1 Β· β±οΈ 21.11.2024):
```
docker pull unum/usearch
```
</details>
<details><summary><b><a href="https://github.com/nmslib/nmslib">NMSLIB</a></b> (π₯30 Β· β 3.4K Β· π) - Non-Metric Space Library (NMSLIB): An efficient similarity search.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/nmslib/nmslib) (π¨βπ» 49 Β· π 450 Β· π¦ 1.3K Β· π 440 - 20% open Β· β±οΈ 21.09.2024):
```
git clone https://github.com/nmslib/nmslib
```
- [PyPi](https://pypi.org/project/nmslib) (π₯ 490K / month Β· π¦ 63 Β· β±οΈ 03.02.2021):
```
pip install nmslib
```
- [Conda](https://anaconda.org/conda-forge/nmslib) (π₯ 170K Β· β±οΈ 09.09.2024):
```
conda install -c conda-forge nmslib
```
</details>
<details><summary><b><a href="https://github.com/lmcinnes/pynndescent">PyNNDescent</a></b> (π₯27 Β· β 910) - A Python nearest neighbor descent for approximate nearest neighbors. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
- [GitHub](https://github.com/lmcinnes/pynndescent) (π¨βπ» 29 Β· π 110 Β· π¦ 8.8K Β· π 140 - 52% open Β· β±οΈ 10.11.2024):
```
git clone https://github.com/lmcinnes/pynndescent
```
- [PyPi](https://pypi.org/project/pynndescent) (π₯ 1.9M / month Β· π¦ 160 Β· β±οΈ 17.06.2024):
```
pip install pynndescent
```
- [Conda](https://anaconda.org/conda-forge/pynndescent) (π₯ 2.1M Β· β±οΈ 14.12.2024):
```
conda install -c conda-forge pynndescent
```
</details>
<details><summary><b><a href="https://github.com/yahoojapan/NGT">NGT</a></b> (π₯23 Β· β 1.3K) - Nearest Neighbor Search with Neighborhood Graph and Tree for High-.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/yahoojapan/NGT) (π¨βπ» 15 Β· π 120 Β· π 140 - 14% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/yahoojapan/NGT
```
- [PyPi](https://pypi.org/project/ngt) (π₯ 3K / month Β· π¦ 8 Β· β±οΈ 06.12.2023):
```
pip install ngt
```
</details>
<details><summary>Show 4 hidden projects...</summary>
- <b><a href="https://github.com/plasticityai/magnitude">Magnitude</a></b> (π₯20 Β· β 1.6K Β· π) - A fast, efficient universal vector embedding utility package. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/pixelogik/NearPy">NearPy</a></b> (π₯20 Β· β 760 Β· π) - Python framework for fast (approximated) nearest neighbour search in.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/kakao/n2">N2</a></b> (π₯20 Β· β 570 Β· π) - TOROS N2 - lightweight approximate Nearest Neighbor library which runs.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/facebookresearch/pysparnn">PySparNN</a></b> (π₯11 Β· β 920 Β· π) - Approximate Nearest Neighbor Search for Sparse Data in Python!. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
</details>
<br>
## Probabilistics & Statistics
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries providing capabilities for probabilistic programming/reasoning, bayesian inference, gaussian processes, or statistics._
<details><summary><b><a href="https://github.com/pymc-devs/pymc">PyMC3</a></b> (π₯41 Β· β 8.8K) - Bayesian Modeling and Probabilistic Programming in Python. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/pymc-devs/pymc) (π¨βπ» 510 Β· π 2K Β· π₯ 2K Β· π¦ 5K Β· π 3.4K - 9% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/pymc-devs/pymc
```
- [PyPi](https://pypi.org/project/pymc3) (π₯ 280K / month Β· π¦ 190 Β· β±οΈ 31.05.2024):
```
pip install pymc3
```
- [Conda](https://anaconda.org/conda-forge/pymc3) (π₯ 620K Β· β±οΈ 02.06.2024):
```
conda install -c conda-forge pymc3
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/probability">tensorflow-probability</a></b> (π₯37 Β· β 4.3K) - Probabilistic reasoning and statistical analysis in.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/probability) (π¨βπ» 500 Β· π 1.1K Β· π¦ 2 Β· π 1.5K - 48% open Β· β±οΈ 09.12.2024):
```
git clone https://github.com/tensorflow/probability
```
- [PyPi](https://pypi.org/project/tensorflow-probability) (π₯ 1.4M / month Β· π¦ 620 Β· β±οΈ 08.11.2024):
```
pip install tensorflow-probability
```
- [Conda](https://anaconda.org/conda-forge/tensorflow-probability) (π₯ 160K Β· β±οΈ 27.05.2024):
```
conda install -c conda-forge tensorflow-probability
```
</details>
<details><summary><b><a href="https://github.com/pgmpy/pgmpy">pgmpy</a></b> (π₯34 Β· β 2.8K) - Python Library for learning (Structure and Parameter), inference.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/pgmpy/pgmpy) (π¨βπ» 130 Β· π 720 Β· π₯ 580 Β· π¦ 1.3K Β· π 950 - 31% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/pgmpy/pgmpy
```
- [PyPi](https://pypi.org/project/pgmpy) (π₯ 110K / month Β· π¦ 53 Β· β±οΈ 09.08.2024):
```
pip install pgmpy
```
</details>
<details><summary><b><a href="https://github.com/pydata/patsy">patsy</a></b> (π₯34 Β· β 960) - Describing statistical models in Python using symbolic formulas. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
- [GitHub](https://github.com/pydata/patsy) (π¨βπ» 22 Β· π 100 Β· π¦ 110K Β· π 160 - 46% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/pydata/patsy
```
- [PyPi](https://pypi.org/project/patsy) (π₯ 15M / month Β· π¦ 530 Β· β±οΈ 12.11.2024):
```
pip install patsy
```
- [Conda](https://anaconda.org/conda-forge/patsy) (π₯ 13M Β· β±οΈ 10.12.2024):
```
conda install -c conda-forge patsy
```
</details>
<details><summary><b><a href="https://github.com/pyro-ppl/pyro">Pyro</a></b> (π₯32 Β· β 8.6K) - Deep universal probabilistic programming with Python and PyTorch. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pyro-ppl/pyro) (π¨βπ» 160 Β· π 990 Β· π 1.1K - 23% open Β· β±οΈ 04.12.2024):
```
git clone https://github.com/pyro-ppl/pyro
```
- [PyPi](https://pypi.org/project/pyro-ppl) (π₯ 290K / month Β· π¦ 190 Β· β±οΈ 02.06.2024):
```
pip install pyro-ppl
```
- [Conda](https://anaconda.org/conda-forge/pyro-ppl) (π₯ 210K Β· β±οΈ 18.12.2024):
```
conda install -c conda-forge pyro-ppl
```
</details>
<details><summary><b><a href="https://github.com/cornellius-gp/gpytorch">GPyTorch</a></b> (π₯32 Β· β 3.6K) - A highly efficient implementation of Gaussian Processes in PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/cornellius-gp/gpytorch) (π¨βπ» 140 Β· π 560 Β· π¦ 2.5K Β· π 1.4K - 27% open Β· β±οΈ 12.12.2024):
```
git clone https://github.com/cornellius-gp/gpytorch
```
- [PyPi](https://pypi.org/project/gpytorch) (π₯ 230K / month Β· π¦ 170 Β· β±οΈ 06.09.2024):
```
pip install gpytorch
```
- [Conda](https://anaconda.org/conda-forge/gpytorch) (π₯ 190K Β· β±οΈ 18.12.2024):
```
conda install -c conda-forge gpytorch
```
</details>
<details><summary><b><a href="https://github.com/hmmlearn/hmmlearn">hmmlearn</a></b> (π₯32 Β· β 3.1K) - Hidden Markov Models in Python, with scikit-learn like API. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/hmmlearn/hmmlearn) (π¨βπ» 49 Β· π 740 Β· π¦ 3K Β· π 450 - 15% open Β· β±οΈ 31.10.2024):
```
git clone https://github.com/hmmlearn/hmmlearn
```
- [PyPi](https://pypi.org/project/hmmlearn) (π₯ 990K / month Β· π¦ 92 Β· β±οΈ 31.10.2024):
```
pip install hmmlearn
```
- [Conda](https://anaconda.org/conda-forge/hmmlearn) (π₯ 310K Β· β±οΈ 31.10.2024):
```
conda install -c conda-forge hmmlearn
```
</details>
<details><summary><b><a href="https://github.com/dfm/emcee">emcee</a></b> (π₯31 Β· β 1.5K) - The Python ensemble sampling toolkit for affine-invariant MCMC. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/dfm/emcee) (π¨βπ» 74 Β· π 430 Β· π¦ 2.7K Β· π 300 - 19% open Β· β±οΈ 07.12.2024):
```
git clone https://github.com/dfm/emcee
```
- [PyPi](https://pypi.org/project/emcee) (π₯ 800K / month Β· π¦ 440 Β· β±οΈ 19.04.2024):
```
pip install emcee
```
- [Conda](https://anaconda.org/conda-forge/emcee) (π₯ 380K Β· β±οΈ 13.12.2024):
```
conda install -c conda-forge emcee
```
</details>
<details><summary><b><a href="https://github.com/SALib/SALib">SALib</a></b> (π₯31 Β· β 890) - Sensitivity Analysis Library in Python. Contains Sobol, Morris, FAST, and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/SALib/SALib) (π¨βπ» 48 Β· π 230 Β· π¦ 1.4K Β· π 340 - 15% open Β· β±οΈ 10.10.2024):
```
git clone https://github.com/SALib/SALib
```
- [PyPi](https://pypi.org/project/salib) (π₯ 920K / month Β· π¦ 130 Β· β±οΈ 19.08.2024):
```
pip install salib
```
- [Conda](https://anaconda.org/conda-forge/salib) (π₯ 200K Β· β±οΈ 20.09.2024):
```
conda install -c conda-forge salib
```
</details>
<details><summary><b><a href="https://github.com/twopirllc/pandas-ta">pandas-ta</a></b> (π₯30 Β· β 5.6K) - Technical Analysis Indicators - Pandas TA is an easy to use.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/twopirllc/pandas-ta) (π¨βπ» 45 Β· π 1.1K Β· π¦ 4.5K Β· π 600 - 17% open Β· β±οΈ 24.06.2024):
```
git clone https://github.com/twopirllc/pandas-ta
```
- [PyPi](https://pypi.org/project/pandas-ta) (π₯ 260K / month Β· π¦ 140 Β· β±οΈ 28.07.2021):
```
pip install pandas-ta
```
- [Conda](https://anaconda.org/conda-forge/pandas-ta) (π₯ 23K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge pandas-ta
```
</details>
<details><summary><b><a href="https://github.com/GPflow/GPflow">GPflow</a></b> (π₯29 Β· β 1.9K) - Gaussian processes in TensorFlow. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/GPflow/GPflow) (π¨βπ» 84 Β· π 440 Β· π¦ 710 Β· π 840 - 18% open Β· β±οΈ 04.10.2024):
```
git clone https://github.com/GPflow/GPflow
```
- [PyPi](https://pypi.org/project/gpflow) (π₯ 70K / month Β· π¦ 35 Β· β±οΈ 17.06.2024):
```
pip install gpflow
```
- [Conda](https://anaconda.org/conda-forge/gpflow) (π₯ 38K Β· β±οΈ 26.06.2024):
```
conda install -c conda-forge gpflow
```
</details>
<details><summary><b><a href="https://github.com/stan-dev/pystan">PyStan</a></b> (π₯28 Β· β 340) - PyStan, a Python interface to Stan, a platform for statistical modeling... <code><a href="http://bit.ly/3hkKRql">ISC</a></code></summary>
- [GitHub](https://github.com/stan-dev/pystan) (π¨βπ» 14 Β· π 59 Β· π¦ 10K Β· π 200 - 6% open Β· β±οΈ 03.07.2024):
```
git clone https://github.com/stan-dev/pystan
```
- [PyPi](https://pypi.org/project/pystan) (π₯ 750K / month Β· π¦ 160 Β· β±οΈ 03.07.2024):
```
pip install pystan
```
- [Conda](https://anaconda.org/conda-forge/pystan):
```
conda install -c conda-forge pystan
```
</details>
<details><summary><b><a href="https://github.com/jmschrei/pomegranate">pomegranate</a></b> (π₯27 Β· β 3.4K) - Fast, flexible and easy to use probabilistic modelling in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/jmschrei/pomegranate) (π¨βπ» 75 Β· π 590 Β· π 780 - 2% open Β· β±οΈ 18.10.2024):
```
git clone https://github.com/jmschrei/pomegranate
```
- [PyPi](https://pypi.org/project/pomegranate) (π₯ 16K / month Β· π¦ 59 Β· β±οΈ 18.10.2024):
```
pip install pomegranate
```
- [Conda](https://anaconda.org/conda-forge/pomegranate) (π₯ 190K Β· β±οΈ 10.12.2023):
```
conda install -c conda-forge pomegranate
```
</details>
<details><summary><b><a href="https://github.com/bambinos/bambi">bambi</a></b> (π₯27 Β· β 1.1K) - BAyesian Model-Building Interface (Bambi) in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/bambinos/bambi) (π¨βπ» 43 Β· π 130 Β· π¦ 160 Β· π 420 - 19% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/bambinos/bambi
```
- [PyPi](https://pypi.org/project/bambi) (π₯ 26K / month Β· π¦ 10 Β· β±οΈ 10.07.2024):
```
pip install bambi
```
- [Conda](https://anaconda.org/conda-forge/bambi) (π₯ 41K Β· β±οΈ 10.07.2024):
```
conda install -c conda-forge bambi
```
</details>
<details><summary><b><a href="https://github.com/maximtrp/scikit-posthocs">scikit-posthocs</a></b> (π₯26 Β· β 350) - Multiple Pairwise Comparisons (Post Hoc) Tests in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/maximtrp/scikit-posthocs) (π¨βπ» 15 Β· π 40 Β· π₯ 66 Β· π¦ 930 Β· π 63 - 4% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/maximtrp/scikit-posthocs
```
- [PyPi](https://pypi.org/project/scikit-posthocs) (π₯ 110K / month Β· π¦ 63 Β· β±οΈ 18.12.2024):
```
pip install scikit-posthocs
```
- [Conda](https://anaconda.org/conda-forge/scikit-posthocs) (π₯ 990K Β· β±οΈ 18.12.2024):
```
conda install -c conda-forge scikit-posthocs
```
</details>
<details><summary><b><a href="https://github.com/uber/orbit">Orbit</a></b> (π₯23 Β· β 1.9K) - A Python package for Bayesian forecasting with object-oriented design.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/uber/orbit) (π¨βπ» 20 Β· π 140 Β· π¦ 64 Β· π 400 - 12% open Β· β±οΈ 10.07.2024):
```
git clone https://github.com/uber/orbit
```
- [PyPi](https://pypi.org/project/orbit-ml) (π₯ 12K / month Β· π¦ 1 Β· β±οΈ 01.04.2024):
```
pip install orbit-ml
```
</details>
<details><summary><b><a href="https://github.com/baal-org/baal">Baal</a></b> (π₯21 Β· β 880) - Bayesian active learning library for research and industrial usecases. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/baal-org/baal) (π¨βπ» 23 Β· π 86 Β· π¦ 62 Β· π 110 - 17% open Β· β±οΈ 27.06.2024):
```
git clone https://github.com/baal-org/baal
```
- [PyPi](https://pypi.org/project/baal) (π₯ 1.9K / month Β· π¦ 2 Β· β±οΈ 11.06.2024):
```
pip install baal
```
- [Conda](https://anaconda.org/conda-forge/baal) (π₯ 11K Β· β±οΈ 12.06.2023):
```
conda install -c conda-forge baal
```
</details>
<details><summary><b><a href="https://github.com/ENSTA-U2IS-AI/torch-uncertainty">TorchUncertainty</a></b> (π₯21 Β· β 320) - Open-source framework for uncertainty and deep.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/ENSTA-U2IS-AI/torch-uncertainty) (π¨βπ» 9 Β· π 20 Β· π 38 - 28% open Β· β±οΈ 19.11.2024):
```
git clone https://github.com/ENSTA-U2IS-AI/torch-uncertainty
```
- [PyPi](https://pypi.org/project/torch-uncertainty) (π₯ 920 / month Β· π¦ 3 Β· β±οΈ 18.11.2024):
```
pip install torch-uncertainty
```
</details>
<details><summary>Show 6 hidden projects...</summary>
- <b><a href="https://github.com/rlabbe/filterpy">filterpy</a></b> (π₯32 Β· β 3.4K Β· π) - Python Kalman filtering and optimal estimation library. Implements.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/raphaelvallat/pingouin">pingouin</a></b> (π₯30 Β· β 1.7K) - Statistical package in Python based on Pandas. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/blei-lab/edward">Edward</a></b> (π₯27 Β· β 4.8K Β· π) - A probabilistic programming language in TensorFlow. Deep.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/mattjj/pyhsmm">pyhsmm</a></b> (π₯21 Β· β 550 Β· π) - Bayesian inference in HSMMs and HMMs. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/pyro-ppl/funsor">Funsor</a></b> (π₯19 Β· β 240 Β· π) - Functional tensors for probabilistic programming. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/thu-ml/zhusuan">ZhuSuan</a></b> (π₯15 Β· β 2.2K Β· π) - A probabilistic programming library for Bayesian deep learning,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
</details>
<br>
## Adversarial Robustness
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for testing the robustness of machine learning models against attacks with adversarial/malicious examples._
<details><summary><b><a href="https://github.com/Trusted-AI/adversarial-robustness-toolbox">ART</a></b> (π₯34 Β· β 5K) - Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/Trusted-AI/adversarial-robustness-toolbox) (π¨βπ» 140 Β· π 1.2K Β· π¦ 630 Β· π 900 - 15% open Β· β±οΈ 13.12.2024):
```
git clone https://github.com/Trusted-AI/adversarial-robustness-toolbox
```
- [PyPi](https://pypi.org/project/adversarial-robustness-toolbox) (π₯ 73K / month Β· π¦ 20 Β· β±οΈ 02.10.2024):
```
pip install adversarial-robustness-toolbox
```
- [Conda](https://anaconda.org/conda-forge/adversarial-robustness-toolbox) (π₯ 57K Β· β±οΈ 03.10.2024):
```
conda install -c conda-forge adversarial-robustness-toolbox
```
</details>
<details><summary><b><a href="https://github.com/QData/TextAttack">TextAttack</a></b> (π₯27 Β· β 3K) - TextAttack is a Python framework for adversarial attacks, data.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/QData/TextAttack) (π¨βπ» 66 Β· π 390 Β· π¦ 330 Β· π 280 - 22% open Β· β±οΈ 25.07.2024):
```
git clone https://github.com/QData/TextAttack
```
- [PyPi](https://pypi.org/project/textattack) (π₯ 6.3K / month Β· π¦ 11 Β· β±οΈ 11.03.2024):
```
pip install textattack
```
- [Conda](https://anaconda.org/conda-forge/textattack) (π₯ 9.1K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge textattack
```
</details>
<details><summary><b><a href="https://github.com/bethgelab/foolbox">Foolbox</a></b> (π₯27 Β· β 2.8K Β· π€) - A Python toolbox to create adversarial examples that fool neural.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/bethgelab/foolbox) (π¨βπ» 35 Β· π 420 Β· π¦ 650 Β· π 380 - 7% open Β· β±οΈ 04.03.2024):
```
git clone https://github.com/bethgelab/foolbox
```
- [PyPi](https://pypi.org/project/foolbox) (π₯ 5.5K / month Β· π¦ 14 Β· β±οΈ 04.03.2024):
```
pip install foolbox
```
- [Conda](https://anaconda.org/conda-forge/foolbox) (π₯ 16K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge foolbox
```
</details>
<details><summary>Show 6 hidden projects...</summary>
- <b><a href="https://github.com/cleverhans-lab/cleverhans">CleverHans</a></b> (π₯29 Β· β 6.2K Β· π) - An adversarial example library for constructing attacks,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/BorealisAI/advertorch">advertorch</a></b> (π₯22 Β· β 1.3K Β· π) - A Toolbox for Adversarial Robustness Research. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/advboxes/AdvBox">AdvBox</a></b> (π₯19 Β· β 1.4K Β· π) - Advbox is a toolbox to generate adversarial examples that fool.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/MadryLab/robustness">robustness</a></b> (π₯19 Β· β 920 Β· π) - A library for experimenting with, training and evaluating neural.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/textflint/textflint">textflint</a></b> (π₯17 Β· β 640 Β· π) - Unified Multilingual Robustness Evaluation Toolkit for.. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code>
- <b><a href="https://github.com/airbnb/artificial-adversary">Adversary</a></b> (π₯15 Β· β 400 Β· π) - Tool to generate adversarial text examples and test machine.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
</details>
<br>
## GPU & Accelerator Utilities
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries that require and make use of CUDA/GPU or other accelerator hardware capabilities to optimize machine learning tasks._
<details><summary><b><a href="https://github.com/cupy/cupy">CuPy</a></b> (π₯39 Β· β 9.6K) - NumPy & SciPy for GPU. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/cupy/cupy) (π¨βπ» 400 Β· π 860 Β· π₯ 190K Β· π¦ 2.4K Β· π 2.4K - 25% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/cupy/cupy
```
- [PyPi](https://pypi.org/project/cupy) (π₯ 63K / month Β· π¦ 270 Β· β±οΈ 22.08.2024):
```
pip install cupy
```
- [Conda](https://anaconda.org/conda-forge/cupy) (π₯ 5.2M Β· β±οΈ 18.10.2024):
```
conda install -c conda-forge cupy
```
- [Docker Hub](https://hub.docker.com/r/cupy/cupy) (π₯ 72K Β· β 13 Β· β±οΈ 22.08.2024):
```
docker pull cupy/cupy
```
</details>
<details><summary><b><a href="https://github.com/huggingface/optimum">optimum</a></b> (π₯36 Β· β 2.6K) - Accelerate inference and training of Transformers, Diffusers, TIMM.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/huggingface/optimum) (π¨βπ» 130 Β· π 470 Β· π¦ 4.1K Β· π 870 - 48% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/huggingface/optimum
```
- [PyPi](https://pypi.org/project/optimum) (π₯ 1.3M / month Β· π¦ 180 Β· β±οΈ 29.10.2024):
```
pip install optimum
```
- [Conda](https://anaconda.org/conda-forge/optimum) (π₯ 29K Β· β±οΈ 29.05.2024):
```
conda install -c conda-forge optimum
```
</details>
<details><summary><b><a href="https://github.com/rapidsai/cudf">cuDF</a></b> (π₯35 Β· β 8.5K) - cuDF - GPU DataFrame Library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/rapidsai/cudf) (π¨βπ» 300 Β· π 910 Β· π¦ 59 Β· π 6.7K - 16% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/rapidsai/cudf
```
- [PyPi](https://pypi.org/project/cudf) (π₯ 3.4K / month Β· π¦ 22 Β· β±οΈ 01.06.2020):
```
pip install cudf
```
</details>
<details><summary><b><a href="https://github.com/inducer/pycuda">PyCUDA</a></b> (π₯32 Β· β 1.9K) - CUDA integration for Python, plus shiny features. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/inducer/pycuda) (π¨βπ» 82 Β· π 290 Β· π¦ 3.3K Β· π 280 - 29% open Β· β±οΈ 05.11.2024):
```
git clone https://github.com/inducer/pycuda
```
- [PyPi](https://pypi.org/project/pycuda) (π₯ 86K / month Β· π¦ 160 Β· β±οΈ 30.07.2024):
```
pip install pycuda
```
- [Conda](https://anaconda.org/conda-forge/pycuda) (π₯ 670K Β· β±οΈ 17.08.2024):
```
conda install -c conda-forge pycuda
```
</details>
<details><summary><b><a href="https://github.com/NVIDIA/apex">Apex</a></b> (π₯31 Β· β 8.5K) - A PyTorch Extension: Tools for easy mixed precision and distributed.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/NVIDIA/apex) (π¨βπ» 130 Β· π 1.4K Β· π¦ 2.9K Β· π 1.3K - 58% open Β· β±οΈ 14.12.2024):
```
git clone https://github.com/NVIDIA/apex
```
- [Conda](https://anaconda.org/conda-forge/nvidia-apex) (π₯ 380K Β· β±οΈ 04.11.2024):
```
conda install -c conda-forge nvidia-apex
```
</details>
<details><summary><b><a href="https://github.com/rapidsai/cuml">cuML</a></b> (π₯31 Β· β 4.3K) - cuML - RAPIDS Machine Learning Library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/rapidsai/cuml) (π¨βπ» 180 Β· π 540 Β· π 2.5K - 36% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/rapidsai/cuml
```
- [PyPi](https://pypi.org/project/cuml) (π₯ 4K / month Β· π¦ 14 Β· β±οΈ 01.06.2020):
```
pip install cuml
```
</details>
<details><summary><b><a href="https://github.com/wookayin/gpustat">gpustat</a></b> (π₯29 Β· β 4.1K Β· π€) - A simple command-line utility for querying and monitoring GPU status. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/wookayin/gpustat) (π¨βπ» 17 Β· π 280 Β· π¦ 6.5K Β· π 120 - 22% open Β· β±οΈ 12.01.2024):
```
git clone https://github.com/wookayin/gpustat
```
- [PyPi](https://pypi.org/project/gpustat) (π₯ 610K / month Β· π¦ 150 Β· β±οΈ 22.08.2023):
```
pip install gpustat
```
- [Conda](https://anaconda.org/conda-forge/gpustat) (π₯ 300K Β· β±οΈ 23.08.2023):
```
conda install -c conda-forge gpustat
```
</details>
<details><summary><b><a href="https://github.com/arrayfire/arrayfire">ArrayFire</a></b> (π₯28 Β· β 4.6K) - ArrayFire: a general purpose GPU library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/arrayfire/arrayfire) (π¨βπ» 95 Β· π 530 Β· π₯ 7.5K Β· π 1.7K - 19% open Β· β±οΈ 12.12.2024):
```
git clone https://github.com/arrayfire/arrayfire
```
- [PyPi](https://pypi.org/project/arrayfire) (π₯ 2.7K / month Β· π¦ 10 Β· β±οΈ 22.02.2022):
```
pip install arrayfire
```
</details>
<details><summary><b><a href="https://github.com/rapidsai/cugraph">cuGraph</a></b> (π₯27 Β· β 1.8K) - cuGraph - RAPIDS Graph Analytics Library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/rapidsai/cugraph) (π¨βπ» 120 Β· π 310 Β· π 1.8K - 10% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/rapidsai/cugraph
```
- [PyPi](https://pypi.org/project/cugraph) (π₯ 370 / month Β· π¦ 4 Β· β±οΈ 01.06.2020):
```
pip install cugraph
```
- [Conda](https://anaconda.org/conda-forge/libcugraph) (π₯ 26K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge libcugraph
```
</details>
<details><summary><b><a href="https://github.com/NVIDIA/DALI">DALI</a></b> (π₯25 Β· β 5.2K) - A GPU-accelerated library containing highly optimized building blocks.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/NVIDIA/DALI) (π¨βπ» 94 Β· π 620 Β· π 1.7K - 14% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/NVIDIA/DALI
```
</details>
<details><summary><b><a href="https://github.com/KomputeProject/kompute">Vulkan Kompute</a></b> (π₯22 Β· β 2K) - General purpose GPU compute framework built on Vulkan to.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/KomputeProject/kompute) (π¨βπ» 31 Β· π 150 Β· π₯ 610 Β· π 220 - 32% open Β· β±οΈ 10.12.2024):
```
git clone https://github.com/KomputeProject/kompute
```
- [PyPi](https://pypi.org/project/kp) (π₯ 300 / month Β· β±οΈ 20.01.2024):
```
pip install kp
```
</details>
<details><summary><b><a href="https://github.com/NVIDIA-Merlin/Merlin">Merlin</a></b> (π₯21 Β· β 790) - NVIDIA Merlin is an open source library providing end-to-end GPU-.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/NVIDIA-Merlin/Merlin) (π¨βπ» 32 Β· π 120 Β· π 460 - 46% open Β· β±οΈ 22.07.2024):
```
git clone https://github.com/NVIDIA-Merlin/Merlin
```
- [PyPi](https://pypi.org/project/merlin-core) (π₯ 9K / month Β· π¦ 1 Β· β±οΈ 29.08.2023):
```
pip install merlin-core
```
</details>
<details><summary>Show 8 hidden projects...</summary>
- <b><a href="https://github.com/anderskm/gputil">GPUtil</a></b> (π₯25 Β· β 1.2K Β· π) - A Python module for getting the GPU status from NVIDA GPUs using.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/lebedov/scikit-cuda">scikit-cuda</a></b> (π₯24 Β· β 990 Β· π) - Python interface to GPU-powered libraries. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/fbcotter/py3nvml">py3nvml</a></b> (π₯22 Β· β 240 Β· π) - Python 3 Bindings for NVML library. Get NVIDIA GPU status inside.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/BlazingDB/blazingsql">BlazingSQL</a></b> (π₯20 Β· β 1.9K Β· π) - BlazingSQL is a lightweight, GPU accelerated, SQL engine for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/nicolargo/nvidia-ml-py3">nvidia-ml-py3</a></b> (π₯18 Β· β 130) - Python 3 Bindings for the NVIDIA Management Library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/rapidsai/cusignal">cuSignal</a></b> (π₯16 Β· β 720 Β· π) - GPU accelerated signal processing. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/Santosh-Gupta/SpeedTorch">SpeedTorch</a></b> (π₯16 Β· β 680 Β· π) - Library for faster pinned CPU - GPU transfer in Pytorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/stas00/ipyexperiments">ipyexperiments</a></b> (π₯16 Β· β 210 Β· π€) - Automatic GPU+CPU memory profiling, re-use and memory.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code>
</details>
<br>
## Tensorflow Utilities
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries that extend TensorFlow with additional capabilities._
<details><summary><b><a href="https://github.com/tensorflow/datasets">TensorFlow Datasets</a></b> (π₯38 Β· β 4.3K) - TFDS is a collection of datasets ready to use with.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/datasets) (π¨βπ» 380 Β· π 1.6K Β· π¦ 21K Β· π 1.5K - 47% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/tensorflow/datasets
```
- [PyPi](https://pypi.org/project/tensorflow-datasets) (π₯ 1.9M / month Β· π¦ 330 Β· β±οΈ 30.10.2024):
```
pip install tensorflow-datasets
```
- [Conda](https://anaconda.org/conda-forge/tensorflow-datasets) (π₯ 41K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge tensorflow-datasets
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/tfx">TFX</a></b> (π₯34 Β· β 2.1K) - TFX is an end-to-end platform for deploying production ML pipelines. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/tfx) (π¨βπ» 190 Β· π 710 Β· π¦ 1.6K Β· π 1.1K - 22% open Β· β±οΈ 12.12.2024):
```
git clone https://github.com/tensorflow/tfx
```
- [PyPi](https://pypi.org/project/tfx) (π₯ 33K / month Β· π¦ 17 Β· β±οΈ 11.12.2024):
```
pip install tfx
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/hub">tensorflow-hub</a></b> (π₯32 Β· β 3.5K) - A library for transfer learning by reusing parts of.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/hub) (π¨βπ» 110 Β· π 1.7K Β· π 710 - 1% open Β· β±οΈ 09.10.2024):
```
git clone https://github.com/tensorflow/hub
```
- [PyPi](https://pypi.org/project/tensorflow-hub) (π₯ 2.1M / month Β· π¦ 300 Β· β±οΈ 30.01.2024):
```
pip install tensorflow-hub
```
- [Conda](https://anaconda.org/conda-forge/tensorflow-hub) (π₯ 110K Β· β±οΈ 07.05.2024):
```
conda install -c conda-forge tensorflow-hub
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/addons">TF Addons</a></b> (π₯31 Β· β 1.7K Β· π€) - Useful extra functionality for TensorFlow 2.x maintained.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/addons) (π¨βπ» 210 Β· π 610 Β· π 990 - 9% open Β· β±οΈ 15.04.2024):
```
git clone https://github.com/tensorflow/addons
```
- [PyPi](https://pypi.org/project/tensorflow-addons) (π₯ 1.2M / month Β· π¦ 370 Β· β±οΈ 28.11.2023):
```
pip install tensorflow-addons
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/io">TensorFlow I/O</a></b> (π₯30 Β· β 710) - Dataset, streaming, and file system extensions.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/io) (π¨βπ» 110 Β· π 290 Β· π 660 - 44% open Β· β±οΈ 01.07.2024):
```
git clone https://github.com/tensorflow/io
```
- [PyPi](https://pypi.org/project/tensorflow-io) (π₯ 1.2M / month Β· π¦ 61 Β· β±οΈ 01.07.2024):
```
pip install tensorflow-io
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/model-optimization">TF Model Optimization</a></b> (π₯29 Β· β 1.5K) - A toolkit to optimize ML models for deployment for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/model-optimization) (π¨βπ» 86 Β· π 320 Β· π 400 - 57% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/tensorflow/model-optimization
```
- [PyPi](https://pypi.org/project/tensorflow-model-optimization) (π₯ 710K / month Β· π¦ 45 Β· β±οΈ 08.02.2024):
```
pip install tensorflow-model-optimization
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/transform">TensorFlow Transform</a></b> (π₯28 Β· β 990) - Input pipeline framework. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/transform) (π¨βπ» 29 Β· π 220 Β· π 210 - 18% open Β· β±οΈ 27.11.2024):
```
git clone https://github.com/tensorflow/transform
```
- [PyPi](https://pypi.org/project/tensorflow-transform) (π₯ 520K / month Β· π¦ 18 Β· β±οΈ 28.10.2024):
```
pip install tensorflow-transform
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/neural-structured-learning">Neural Structured Learning</a></b> (π₯24 Β· β 990) - Training neural models with structured signals. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/neural-structured-learning) (π¨βπ» 38 Β· π 190 Β· π¦ 490 Β· π 69 - 1% open Β· β±οΈ 18.06.2024):
```
git clone https://github.com/tensorflow/neural-structured-learning
```
- [PyPi](https://pypi.org/project/neural-structured-learning) (π₯ 6.1K / month Β· π¦ 3 Β· β±οΈ 29.07.2022):
```
pip install neural-structured-learning
```
</details>
<details><summary><b><a href="https://github.com/PAIR-code/saliency">Saliency</a></b> (π₯22 Β· β 960 Β· π€) - Framework-agnostic implementation for state-of-the-art.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/PAIR-code/saliency) (π¨βπ» 18 Β· π 190 Β· π¦ 120 Β· π 39 - 30% open Β· β±οΈ 20.03.2024):
```
git clone https://github.com/PAIR-code/saliency
```
- [PyPi](https://pypi.org/project/saliency) (π₯ 14K / month Β· π¦ 8 Β· β±οΈ 20.03.2024):
```
pip install saliency
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/compression">TF Compression</a></b> (π₯22 Β· β 860) - Data compression in TensorFlow. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/compression) (π¨βπ» 24 Β· π 250 Β· π 100 - 10% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/tensorflow/compression
```
- [PyPi](https://pypi.org/project/tensorflow-compression) (π₯ 2.3K / month Β· π¦ 2 Β· β±οΈ 02.02.2024):
```
pip install tensorflow-compression
```
</details>
<details><summary><b><a href="https://github.com/tensorflow/cloud">TensorFlow Cloud</a></b> (π₯21 Β· β 380 Β· π€) - The TensorFlow Cloud repository provides APIs that.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tensorflow/cloud) (π¨βπ» 27 Β· π 90 Β· π 100 - 73% open Β· β±οΈ 25.02.2024):
```
git clone https://github.com/tensorflow/cloud
```
- [PyPi](https://pypi.org/project/tensorflow-cloud) (π₯ 37K / month Β· π¦ 7 Β· β±οΈ 17.06.2021):
```
pip install tensorflow-cloud
```
</details>
<details><summary>Show 5 hidden projects...</summary>
- <b><a href="https://github.com/tensorflow/tensor2tensor">tensor2tensor</a></b> (π₯33 Β· β 16K Β· π) - Library of deep learning models and datasets designed.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/keras-team/keras-preprocessing">Keras-Preprocessing</a></b> (π₯28 Β· β 1K Β· π) - Utilities for working with image data, text data, and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/qubvel/efficientnet">efficientnet</a></b> (π₯26 Β· β 2.1K Β· π) - Implementation of EfficientNet model. Keras and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/taehoonlee/tensornets">TensorNets</a></b> (π₯20 Β· β 1K Β· π) - High level network definitions with pre-trained weights in.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/geffy/tffm">tffm</a></b> (π₯18 Β· β 780 Β· π) - TensorFlow implementation of an arbitrary order Factorization Machine. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code>
</details>
<br>
## Jax Utilities
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries that extend Jax with additional capabilities._
<details><summary><b><a href="https://github.com/patrick-kidger/equinox">equinox</a></b> (π₯31 Β· β 2.2K) - Elegant easy-to-use neural networks + scientific computing in.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/patrick-kidger/equinox) (π¨βπ» 56 Β· π 140 Β· π¦ 890 Β· π 480 - 34% open Β· β±οΈ 08.12.2024):
```
git clone https://github.com/patrick-kidger/equinox
```
- [PyPi](https://pypi.org/project/equinox) (π₯ 310K / month Β· π¦ 200 Β· β±οΈ 08.12.2024):
```
pip install equinox
```
</details>
<details><summary><b><a href="https://github.com/google/evojax">evojax</a></b> (π₯19 Β· β 860) - EvoJAX: Hardware-accelerated Neuroevolution. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/google/evojax) (π¨βπ» 14 Β· π 89 Β· π¦ 27 Β· π 37 - 54% open Β· β±οΈ 27.06.2024):
```
git clone https://github.com/google/evojax
```
- [PyPi](https://pypi.org/project/evojax) (π₯ 1.4K / month Β· π¦ 6 Β· β±οΈ 18.06.2024):
```
pip install evojax
```
- [Conda](https://anaconda.org/conda-forge/evojax) (π₯ 33K Β· β±οΈ 18.06.2024):
```
conda install -c conda-forge evojax
```
</details>
<details><summary>Show 1 hidden projects...</summary>
- <b><a href="https://github.com/ucl-bug/jaxdf">jaxdf</a></b> (π₯12 Β· β 120) - A JAX-based research framework for writing differentiable.. <code><a href="http://bit.ly/37RvQcA">βοΈLGPL-3.0</a></code> <code><img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13"></code>
</details>
<br>
## Sklearn Utilities
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries that extend scikit-learn with additional capabilities._
<details><summary><b><a href="https://github.com/rasbt/mlxtend">MLxtend</a></b> (π₯35 Β· β 4.9K) - A library of extension and helper modules for Pythons data.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/rasbt/mlxtend) (π¨βπ» 110 Β· π 870 Β· π¦ 17K Β· π 490 - 29% open Β· β±οΈ 15.11.2024):
```
git clone https://github.com/rasbt/mlxtend
```
- [PyPi](https://pypi.org/project/mlxtend) (π₯ 830K / month Β· π¦ 190 Β· β±οΈ 15.11.2024):
```
pip install mlxtend
```
- [Conda](https://anaconda.org/conda-forge/mlxtend) (π₯ 330K Β· β±οΈ 16.11.2024):
```
conda install -c conda-forge mlxtend
```
</details>
<details><summary><b><a href="https://github.com/uxlfoundation/scikit-learn-intelex">scikit-learn-intelex</a></b> (π₯35 Β· β 1.2K) - Extension for Scikit-learn is a seamless way to speed.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/uxlfoundation/scikit-learn-intelex) (π¨βπ» 83 Β· π 180 Β· π¦ 13K Β· π 240 - 18% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/intel/scikit-learn-intelex
```
- [PyPi](https://pypi.org/project/scikit-learn-intelex) (π₯ 180K / month Β· π¦ 55 Β· β±οΈ 12.12.2024):
```
pip install scikit-learn-intelex
```
- [Conda](https://anaconda.org/conda-forge/scikit-learn-intelex) (π₯ 390K Β· β±οΈ 13.11.2024):
```
conda install -c conda-forge scikit-learn-intelex
```
</details>
<details><summary><b><a href="https://github.com/scikit-learn-contrib/imbalanced-learn">imbalanced-learn</a></b> (π₯33 Β· β 6.9K) - A Python Package to Tackle the Curse of Imbalanced.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/scikit-learn-contrib/imbalanced-learn) (π¨βπ» 85 Β· π 1.3K Β· π 620 - 7% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/scikit-learn-contrib/imbalanced-learn
```
- [PyPi](https://pypi.org/project/imbalanced-learn) (π₯ 16M / month Β· π¦ 450 Β· β±οΈ 04.10.2024):
```
pip install imbalanced-learn
```
- [Conda](https://anaconda.org/conda-forge/imbalanced-learn) (π₯ 640K Β· β±οΈ 04.10.2024):
```
conda install -c conda-forge imbalanced-learn
```
</details>
<details><summary><b><a href="https://github.com/scikit-learn-contrib/category_encoders">category_encoders</a></b> (π₯32 Β· β 2.4K) - A library of sklearn compatible categorical variable.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/scikit-learn-contrib/category_encoders) (π¨βπ» 70 Β· π 400 Β· π¦ 2.4K Β· π 290 - 15% open Β· β±οΈ 01.10.2024):
```
git clone https://github.com/scikit-learn-contrib/category_encoders
```
- [PyPi](https://pypi.org/project/category_encoders) (π₯ 1.5M / month Β· π¦ 280 Β· β±οΈ 01.10.2024):
```
pip install category_encoders
```
- [Conda](https://anaconda.org/conda-forge/category_encoders) (π₯ 290K Β· β±οΈ 02.10.2024):
```
conda install -c conda-forge category_encoders
```
</details>
<details><summary><b><a href="https://github.com/koaning/scikit-lego">scikit-lego</a></b> (π₯28 Β· β 1.3K) - Extra blocks for scikit-learn pipelines. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/koaning/scikit-lego) (π¨βπ» 68 Β· π 120 Β· π¦ 170 Β· π 330 - 12% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/koaning/scikit-lego
```
- [PyPi](https://pypi.org/project/scikit-lego) (π₯ 26K / month Β· π¦ 13 Β· β±οΈ 17.12.2024):
```
pip install scikit-lego
```
- [Conda](https://anaconda.org/conda-forge/scikit-lego) (π₯ 60K Β· β±οΈ 10.07.2024):
```
conda install -c conda-forge scikit-lego
```
</details>
<details><summary><b><a href="https://github.com/guofei9987/scikit-opt">scikit-opt</a></b> (π₯25 Β· β 5.3K) - Genetic Algorithm, Particle Swarm Optimization, Simulated.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/guofei9987/scikit-opt) (π¨βπ» 24 Β· π 990 Β· π¦ 240 Β· π 180 - 37% open Β· β±οΈ 23.06.2024):
```
git clone https://github.com/guofei9987/scikit-opt
```
- [PyPi](https://pypi.org/project/scikit-opt) (π₯ 4.9K / month Β· π¦ 15 Β· β±οΈ 14.01.2022):
```
pip install scikit-opt
```
</details>
<details><summary><b><a href="https://github.com/trent-b/iterative-stratification">iterative-stratification</a></b> (π₯23 Β· β 850) - scikit-learn cross validators for iterative.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/trent-b/iterative-stratification) (π¨βπ» 7 Β· π 75 Β· π¦ 520 Β· π 27 - 7% open Β· β±οΈ 12.10.2024):
```
git clone https://github.com/trent-b/iterative-stratification
```
- [PyPi](https://pypi.org/project/iterative-stratification) (π₯ 46K / month Β· π¦ 15 Β· β±οΈ 12.10.2024):
```
pip install iterative-stratification
```
</details>
<details><summary><b><a href="https://github.com/amueller/dabl">dabl</a></b> (π₯20 Β· β 730) - Data Analysis Baseline Library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/amueller/dabl) (π¨βπ» 24 Β· π 100 Β· β±οΈ 07.08.2024):
```
git clone https://github.com/amueller/dabl
```
- [PyPi](https://pypi.org/project/dabl) (π₯ 5.8K / month Β· π¦ 3 Β· β±οΈ 16.12.2024):
```
pip install dabl
```
</details>
<details><summary><b><a href="https://github.com/scikit-tda/scikit-tda">scikit-tda</a></b> (π₯19 Β· β 530) - Topological Data Analysis for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/scikit-tda/scikit-tda) (π¨βπ» 6 Β· π 55 Β· π¦ 65 Β· π 22 - 18% open Β· β±οΈ 19.07.2024):
```
git clone https://github.com/scikit-tda/scikit-tda
```
- [PyPi](https://pypi.org/project/scikit-tda) (π₯ 1.2K / month Β· β±οΈ 19.07.2024):
```
pip install scikit-tda
```
</details>
<details><summary><b><a href="https://github.com/scikit-learn-contrib/DESlib">DESlib</a></b> (π₯18 Β· β 480 Β· π€) - A Python library for dynamic classifier and ensemble selection. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/scikit-learn-contrib/DESlib) (π¨βπ» 17 Β· π 100 Β· π 160 - 11% open Β· β±οΈ 15.04.2024):
```
git clone https://github.com/scikit-learn-contrib/DESlib
```
- [PyPi](https://pypi.org/project/deslib) (π₯ 3.8K / month Β· π¦ 3 Β· β±οΈ 12.04.2024):
```
pip install deslib
```
</details>
<details><summary>Show 9 hidden projects...</summary>
- <b><a href="https://github.com/sebp/scikit-survival">scikit-survival</a></b> (π₯31 Β· β 1.1K) - Survival analysis built on top of scikit-learn. <code><a href="http://bit.ly/2M0xdwT">βοΈGPL-3.0</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/iskandr/fancyimpute">fancyimpute</a></b> (π₯27 Β· β 1.3K Β· π) - Multivariate imputation and matrix completion.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/scikit-multilearn/scikit-multilearn">scikit-multilearn</a></b> (π₯27 Β· β 920 Β· π) - A scikit-learn based module for multi-label et. al... <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/TeamHG-Memex/sklearn-crfsuite">sklearn-crfsuite</a></b> (π₯26 Β· β 430 Β· π) - scikit-learn inspired API for CRFsuite. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/scikit-learn-contrib/lightning">sklearn-contrib-lightning</a></b> (π₯22 Β· β 1.7K Β· π) - Large-scale linear classification, regression and.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/yzhao062/combo">combo</a></b> (π₯21 Β· β 640 Β· π) - (AAAI 20) A Python Toolbox for Machine Learning Model.. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code> <code>xgboost</code>
- <b><a href="https://github.com/scikit-learn-contrib/skope-rules">skope-rules</a></b> (π₯21 Β· β 620 Β· π) - machine learning with logical rules in Python. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">βοΈBSD-1-Clause</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/mathurinm/celer">celer</a></b> (π₯20 Β· β 210) - Fast solver for L1-type problems: Lasso, sparse Logisitic regression,.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/skggm/skggm">skggm</a></b> (π₯17 Β· β 240 Β· π) - Scikit-learn compatible estimation of general graphical models. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
</details>
<br>
## Pytorch Utilities
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries that extend Pytorch with additional capabilities._
<details><summary><b><a href="https://github.com/huggingface/accelerate">accelerate</a></b> (π₯40 Β· β 8.1K) - A simple way to launch, train, and use PyTorch models on.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/huggingface/accelerate) (π¨βπ» 310 Β· π 990 Β· π¦ 63K Β· π 1.7K - 7% open Β· β±οΈ 13.12.2024):
```
git clone https://github.com/huggingface/accelerate
```
- [PyPi](https://pypi.org/project/accelerate) (π₯ 8.4M / month Β· π¦ 1.7K Β· β±οΈ 13.12.2024):
```
pip install accelerate
```
- [Conda](https://anaconda.org/conda-forge/accelerate) (π₯ 260K Β· β±οΈ 16.12.2024):
```
conda install -c conda-forge accelerate
```
</details>
<details><summary><b><a href="https://github.com/KevinMusgrave/pytorch-metric-learning">PML</a></b> (π₯35 Β· β 6K) - The easiest way to use deep metric learning in your application. Modular,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/KevinMusgrave/pytorch-metric-learning) (π¨βπ» 43 Β· π 660 Β· π¦ 2.1K Β· π 520 - 13% open Β· β±οΈ 11.12.2024):
```
git clone https://github.com/KevinMusgrave/pytorch-metric-learning
```
- [PyPi](https://pypi.org/project/pytorch-metric-learning) (π₯ 850K / month Β· π¦ 55 Β· β±οΈ 11.12.2024):
```
pip install pytorch-metric-learning
```
- [Conda](https://anaconda.org/metric-learning/pytorch-metric-learning) (π₯ 12K Β· β±οΈ 16.06.2023):
```
conda install -c metric-learning pytorch-metric-learning
```
</details>
<details><summary><b><a href="https://github.com/tinygrad/tinygrad">tinygrad</a></b> (π₯33 Β· β 27K) - You like pytorch? You like micrograd? You love tinygrad!. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/tinygrad/tinygrad) (π¨βπ» 360 Β· π 3K Β· π¦ 150 Β· π 830 - 16% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/geohot/tinygrad
```
</details>
<details><summary><b><a href="https://github.com/rtqichen/torchdiffeq">torchdiffeq</a></b> (π₯31 Β· β 5.7K) - Differentiable ODE solvers with full GPU support and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/rtqichen/torchdiffeq) (π¨βπ» 21 Β· π 930 Β· π¦ 4.3K Β· π 220 - 33% open Β· β±οΈ 21.11.2024):
```
git clone https://github.com/rtqichen/torchdiffeq
```
- [PyPi](https://pypi.org/project/torchdiffeq) (π₯ 760K / month Β· π¦ 120 Β· β±οΈ 21.11.2024):
```
pip install torchdiffeq
```
- [Conda](https://anaconda.org/conda-forge/torchdiffeq) (π₯ 19K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge torchdiffeq
```
</details>
<details><summary><b><a href="https://github.com/BloodAxe/pytorch-toolbelt">Pytorch Toolbelt</a></b> (π₯26 Β· β 1.5K) - PyTorch extensions for fast R&D prototyping and Kaggle.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/BloodAxe/pytorch-toolbelt) (π¨βπ» 8 Β· π 120 Β· π₯ 130 Β· π 33 - 12% open Β· β±οΈ 21.11.2024):
```
git clone https://github.com/BloodAxe/pytorch-toolbelt
```
- [PyPi](https://pypi.org/project/pytorch_toolbelt) (π₯ 8.5K / month Β· π¦ 12 Β· β±οΈ 21.11.2024):
```
pip install pytorch_toolbelt
```
</details>
<details><summary><b><a href="https://github.com/rusty1s/pytorch_scatter">torch-scatter</a></b> (π₯25 Β· β 1.6K) - PyTorch Extension Library of Optimized Scatter Operations. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/rusty1s/pytorch_scatter) (π¨βπ» 31 Β· π 180 Β· π 400 - 7% open Β· β±οΈ 02.12.2024):
```
git clone https://github.com/rusty1s/pytorch_scatter
```
- [PyPi](https://pypi.org/project/torch-scatter) (π₯ 40K / month Β· π¦ 150 Β· β±οΈ 06.10.2023):
```
pip install torch-scatter
```
- [Conda](https://anaconda.org/conda-forge/pytorch_scatter) (π₯ 580K Β· β±οΈ 05.11.2024):
```
conda install -c conda-forge pytorch_scatter
```
</details>
<details><summary><b><a href="https://github.com/rwightman/gen-efficientnet-pytorch">EfficientNets</a></b> (π₯25 Β· β 1.6K) - Pretrained EfficientNet, EfficientNet-Lite, MixNet,.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/rwightman/gen-efficientnet-pytorch) (π¨βπ» 5 Β· π 210 Β· π¦ 270 Β· π 55 - 7% open Β· β±οΈ 13.06.2024):
```
git clone https://github.com/rwightman/gen-efficientnet-pytorch
```
- [PyPi](https://pypi.org/project/geffnet) (π₯ 150K / month Β· π¦ 4 Β· β±οΈ 08.07.2021):
```
pip install geffnet
```
</details>
<details><summary><b><a href="https://github.com/rusty1s/pytorch_sparse">PyTorch Sparse</a></b> (π₯23 Β· β 1K) - PyTorch Extension Library of Optimized Autograd Sparse Matrix.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/rusty1s/pytorch_sparse) (π¨βπ» 45 Β· π 150 Β· π 280 - 10% open Β· β±οΈ 12.11.2024):
```
git clone https://github.com/rusty1s/pytorch_sparse
```
- [PyPi](https://pypi.org/project/torch-sparse) (π₯ 29K / month Β· π¦ 120 Β· β±οΈ 06.10.2023):
```
pip install torch-sparse
```
- [Conda](https://anaconda.org/conda-forge/pytorch_sparse) (π₯ 540K Β· β±οΈ 05.11.2024):
```
conda install -c conda-forge pytorch_sparse
```
</details>
<details><summary>Show 24 hidden projects...</summary>
- <b><a href="https://github.com/google-research/torchsde">torchsde</a></b> (π₯30 Β· β 1.6K Β· π) - Differentiable SDE solvers with GPU support and efficient.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/Cadene/pretrained-models.pytorch">pretrainedmodels</a></b> (π₯29 Β· β 9K Β· π) - Pretrained ConvNets for pytorch: NASNet, ResNeXt,.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/sksq96/pytorch-summary">pytorch-summary</a></b> (π₯28 Β· β 4K Β· π) - Model summary in PyTorch similar to `model.summary()` in.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/lukemelas/EfficientNet-PyTorch">EfficientNet-PyTorch</a></b> (π₯27 Β· β 8K Β· π) - A PyTorch implementation of EfficientNet. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/Lightning-Universe/lightning-flash">lightning-flash</a></b> (π₯27 Β· β 1.7K Β· π) - Your PyTorch AI Factory - Flash enables you to easily.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/jettify/pytorch-optimizer">pytorch-optimizer</a></b> (π₯26 Β· β 3.1K Β· π) - torch-optimizer -- collection of optimizers for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/dreamquark-ai/tabnet">TabNet</a></b> (π₯26 Β· β 2.7K Β· π) - PyTorch implementation of TabNet paper :.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/facebookresearch/higher">Higher</a></b> (π₯24 Β· β 1.6K Β· π) - higher is a pytorch library allowing users to obtain higher.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/tristandeleu/pytorch-meta">Torchmeta</a></b> (π₯23 Β· β 2K Β· π) - A collection of extensions and data-loaders for few-shot.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/karpathy/micrograd">micrograd</a></b> (π₯22 Β· β 11K Β· π) - A tiny scalar-valued autograd engine and a neural net library.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/asappresearch/sru">SRU</a></b> (π₯22 Β· β 2.1K Β· π) - Training RNNs as Fast as CNNs (https://arxiv.org/abs/1709.02755). <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/adobe/antialiased-cnns">Antialiased CNNs</a></b> (π₯22 Β· β 1.7K Β· π) - pip install antialiased-cnns to improve stability and.. <code><a href="https://tldrlegal.com/search?q=CC%20BY-NC-SA%204.0">βοΈCC BY-NC-SA 4.0</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/Luolc/AdaBound">AdaBound</a></b> (π₯21 Β· β 2.9K Β· π) - An optimizer that trains as fast as Adam and as good as SGD. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/lucidrains/reformer-pytorch">reformer-pytorch</a></b> (π₯21 Β· β 2.1K Β· π) - Reformer, the efficient Transformer, in Pytorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/GRAAL-Research/poutyne">Poutyne</a></b> (π₯21 Β· β 570) - A simplified framework and utilities for PyTorch. <code><a href="http://bit.ly/37RvQcA">βοΈLGPL-3.0</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/lucidrains/lambda-networks">Lambda Networks</a></b> (π₯20 Β· β 1.5K Β· π) - Implementation of LambdaNetworks, a new approach to.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/lucidrains/performer-pytorch">Performer Pytorch</a></b> (π₯20 Β· β 1.1K Β· π) - An implementation of Performer, a linear attention-.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/szagoruyko/pytorchviz">pytorchviz</a></b> (π₯19 Β· β 3.3K Β· π) - A small package to create visualizations of PyTorch execution.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/harvardnlp/pytorch-struct">Torch-Struct</a></b> (π₯18 Β· β 1.1K Β· π) - Fast, general, and tested differentiable structured.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/abhishekkrthakur/tez">Tez</a></b> (π₯17 Β· β 1.2K Β· π) - Tez is a super-simple and lightweight Trainer for PyTorch. It.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/parrt/tensor-sensor">Tensor Sensor</a></b> (π₯17 Β· β 800 Β· π) - The goal of this library is to generate more helpful.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/facebookresearch/madgrad">madgrad</a></b> (π₯16 Β· β 800 Β· π) - MADGRAD Optimization Method. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/achaiah/pywick">Pywick</a></b> (π₯16 Β· β 400 Β· π) - High-level batteries-included neural network training library for.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/TorchDrift/TorchDrift">TorchDrift</a></b> (π₯15 Β· β 310 Β· π) - Drift Detection for your PyTorch Models. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
</details>
<br>
## Database Clients
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
_Libraries for connecting to, operating, and querying databases._
π <b><a href="https://github.com/ml-tooling/best-of-python#database-clients">best-of-python - DB Clients</a></b> ( β 3.7K) - Collection of database clients for python.
<br>
## Others
<a href="#contents"><img align="right" width="15" height="15" src="https://git.io/JtehR" alt="Back to top"></a>
<details><summary><b><a href="https://github.com/scipy/scipy">scipy</a></b> (π₯50 Β· β 13K) - Ecosystem of open-source software for mathematics, science, and engineering. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/scipy/scipy) (π¨βπ» 1.7K Β· π 5.2K Β· π₯ 440K Β· π¦ 1.2M Β· π 11K - 15% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/scipy/scipy
```
- [PyPi](https://pypi.org/project/scipy) (π₯ 120M / month Β· π¦ 48K Β· β±οΈ 13.12.2024):
```
pip install scipy
```
- [Conda](https://anaconda.org/conda-forge/scipy) (π₯ 56M Β· β±οΈ 08.12.2024):
```
conda install -c conda-forge scipy
```
</details>
<details><summary><b><a href="https://github.com/sympy/sympy">SymPy</a></b> (π₯49 Β· β 13K) - A computer algebra system written in pure Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/sympy/sympy) (π¨βπ» 1.3K Β· π 4.5K Β· π₯ 550K Β· π¦ 200K Β· π 14K - 36% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/sympy/sympy
```
- [PyPi](https://pypi.org/project/sympy) (π₯ 32M / month Β· π¦ 3.5K Β· β±οΈ 18.09.2024):
```
pip install sympy
```
- [Conda](https://anaconda.org/conda-forge/sympy) (π₯ 7.4M Β· β±οΈ 09.10.2024):
```
conda install -c conda-forge sympy
```
</details>
<details><summary><b><a href="https://github.com/streamlit/streamlit">Streamlit</a></b> (π₯46 Β· β 36K) - Streamlit A faster way to build and share data apps. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/streamlit/streamlit) (π¨βπ» 260 Β· π 3.1K Β· π¦ 630K Β· π 4.8K - 20% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/streamlit/streamlit
```
- [PyPi](https://pypi.org/project/streamlit) (π₯ 7.7M / month Β· π¦ 3K Β· β±οΈ 13.12.2024):
```
pip install streamlit
```
</details>
<details><summary><b><a href="https://github.com/gradio-app/gradio">Gradio</a></b> (π₯44 Β· β 35K) - Wrap UIs around any model, share with anyone. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/gradio-app/gradio) (π¨βπ» 480 Β· π 2.6K Β· π¦ 50K Β· π 5.1K - 8% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/gradio-app/gradio
```
- [PyPi](https://pypi.org/project/gradio) (π₯ 6.4M / month Β· π¦ 930 Β· β±οΈ 16.12.2024):
```
pip install gradio
```
</details>
<details><summary><b><a href="https://github.com/carla-simulator/carla">carla</a></b> (π₯37 Β· β 12K Β· π) - Open-source simulator for autonomous driving research. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/carla-simulator/carla) (π¨βπ» 200 Β· π 3.7K Β· π¦ 880 Β· π 5.7K - 19% open Β· β±οΈ 17.12.2024):
```
git clone https://github.com/carla-simulator/carla
```
- [PyPi](https://pypi.org/project/carla) (π₯ 15K / month Β· π¦ 11 Β· β±οΈ 14.11.2023):
```
pip install carla
```
</details>
<details><summary><b><a href="https://github.com/HIPS/autograd">Autograd</a></b> (π₯37 Β· β 7.1K) - Efficiently computes derivatives of NumPy code. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/HIPS/autograd) (π¨βπ» 60 Β· π 910 Β· π¦ 11K Β· π 420 - 42% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/HIPS/autograd
```
- [PyPi](https://pypi.org/project/autograd) (π₯ 4.7M / month Β· π¦ 280 Β· β±οΈ 22.08.2024):
```
pip install autograd
```
- [Conda](https://anaconda.org/conda-forge/autograd) (π₯ 500K Β· β±οΈ 13.12.2024):
```
conda install -c conda-forge autograd
```
</details>
<details><summary><b><a href="https://github.com/PennyLaneAI/pennylane">PennyLane</a></b> (π₯37 Β· β 2.4K) - PennyLane is a cross-platform Python library for quantum.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/PennyLaneAI/pennylane) (π¨βπ» 190 Β· π 610 Β· π₯ 100 Β· π¦ 1.2K Β· π 1.5K - 23% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/PennyLaneAI/PennyLane
```
- [PyPi](https://pypi.org/project/pennylane) (π₯ 72K / month Β· π¦ 120 Β· β±οΈ 05.11.2024):
```
pip install pennylane
```
- [Conda](https://anaconda.org/conda-forge/pennylane):
```
conda install -c conda-forge pennylane
```
</details>
<details><summary><b><a href="https://github.com/yzhao062/pyod">PyOD</a></b> (π₯35 Β· β 8.7K) - A Python Library for Outlier and Anomaly Detection, Integrating Classical.. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
- [GitHub](https://github.com/yzhao062/pyod) (π¨βπ» 60 Β· π 1.4K Β· π¦ 4.6K Β· π 370 - 60% open Β· β±οΈ 12.11.2024):
```
git clone https://github.com/yzhao062/pyod
```
- [PyPi](https://pypi.org/project/pyod) (π₯ 690K / month Β· π¦ 110 Β· β±οΈ 06.09.2024):
```
pip install pyod
```
- [Conda](https://anaconda.org/conda-forge/pyod) (π₯ 130K Β· β±οΈ 06.09.2024):
```
conda install -c conda-forge pyod
```
</details>
<details><summary><b><a href="https://github.com/deepchem/deepchem">DeepChem</a></b> (π₯35 Β· β 5.6K) - Democratizing Deep-Learning for Drug Discovery, Quantum Chemistry,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/deepchem/deepchem) (π¨βπ» 250 Β· π 1.7K Β· π¦ 470 Β· π 1.9K - 34% open Β· β±οΈ 18.12.2024):
```
git clone https://github.com/deepchem/deepchem
```
- [PyPi](https://pypi.org/project/deepchem) (π₯ 59K / month Β· π¦ 14 Β· β±οΈ 18.12.2024):
```
pip install deepchem
```
- [Conda](https://anaconda.org/conda-forge/deepchem) (π₯ 110K Β· β±οΈ 05.04.2024):
```
conda install -c conda-forge deepchem
```
</details>
<details><summary><b><a href="https://github.com/wireservice/agate">agate</a></b> (π₯35 Β· β 1.2K) - A Python data analysis library that is optimized for humans instead of.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/wireservice/agate) (π¨βπ» 53 Β· π 160 Β· π¦ 4.2K Β· π 650 - 0% open Β· β±οΈ 30.07.2024):
```
git clone https://github.com/wireservice/agate
```
- [PyPi](https://pypi.org/project/agate) (π₯ 14M / month Β· π¦ 49 Β· β±οΈ 30.07.2024):
```
pip install agate
```
- [Conda](https://anaconda.org/conda-forge/agate) (π₯ 260K Β· β±οΈ 17.12.2024):
```
conda install -c conda-forge agate
```
</details>
<details><summary><b><a href="https://github.com/simonw/datasette">Datasette</a></b> (π₯34 Β· β 9.6K) - An open source multi-tool for exploring and publishing data. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/simonw/datasette) (π¨βπ» 80 Β· π 690 Β· π₯ 69 Β· π¦ 1.4K Β· π 1.9K - 32% open Β· β±οΈ 29.11.2024):
```
git clone https://github.com/simonw/datasette
```
- [PyPi](https://pypi.org/project/datasette) (π₯ 210K / month Β· π¦ 420 Β· β±οΈ 29.11.2024):
```
pip install datasette
```
- [Conda](https://anaconda.org/conda-forge/datasette) (π₯ 50K Β· β±οΈ 30.11.2024):
```
conda install -c conda-forge datasette
```
</details>
<details><summary><b><a href="https://github.com/scikit-learn-contrib/hdbscan">hdbscan</a></b> (π₯34 Β· β 2.8K) - A high performance implementation of HDBSCAN clustering. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/scikit-learn-contrib/hdbscan) (π¨βπ» 96 Β· π 500 Β· π¦ 4.5K Β· π 530 - 67% open Β· β±οΈ 18.11.2024):
```
git clone https://github.com/scikit-learn-contrib/hdbscan
```
- [PyPi](https://pypi.org/project/hdbscan) (π₯ 840K / month Β· π¦ 350 Β· β±οΈ 18.11.2024):
```
pip install hdbscan
```
- [Conda](https://anaconda.org/conda-forge/hdbscan) (π₯ 2.3M Β· β±οΈ 12.10.2024):
```
conda install -c conda-forge hdbscan
```
</details>
<details><summary><b><a href="https://github.com/serge-sans-paille/pythran">Pythran</a></b> (π₯33 Β· β 2K) - Ahead of Time compiler for numeric kernels. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/serge-sans-paille/pythran) (π¨βπ» 73 Β· π 190 Β· π¦ 2.9K Β· π 880 - 15% open Β· β±οΈ 13.12.2024):
```
git clone https://github.com/serge-sans-paille/pythran
```
- [PyPi](https://pypi.org/project/pythran) (π₯ 390K / month Β· π¦ 21 Β· β±οΈ 31.10.2024):
```
pip install pythran
```
- [Conda](https://anaconda.org/conda-forge/pythran) (π₯ 790K Β· β±οΈ 23.11.2024):
```
conda install -c conda-forge pythran
```
</details>
<details><summary><b><a href="https://github.com/datalad/datalad">datalad</a></b> (π₯33 Β· β 550) - Keep code, data, containers under control with git and git-annex. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/datalad/datalad) (π¨βπ» 57 Β· π 110 Β· π¦ 440 Β· π 4K - 13% open Β· β±οΈ 15.12.2024):
```
git clone https://github.com/datalad/datalad
```
- [PyPi](https://pypi.org/project/datalad) (π₯ 49K / month Β· π¦ 99 Β· β±οΈ 15.12.2024):
```
pip install datalad
```
- [Conda](https://anaconda.org/conda-forge/datalad) (π₯ 690K Β· β±οΈ 20.11.2024):
```
conda install -c conda-forge datalad
```
</details>
<details><summary><b><a href="https://github.com/online-ml/river">River</a></b> (π₯32 Β· β 5.1K) - Online machine learning in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/online-ml/river) (π¨βπ» 120 Β· π 550 Β· π¦ 610 Β· π 620 - 19% open Β· β±οΈ 06.12.2024):
```
git clone https://github.com/online-ml/river
```
- [PyPi](https://pypi.org/project/river) (π₯ 91K / month Β· π¦ 64 Β· β±οΈ 25.11.2024):
```
pip install river
```
- [Conda](https://anaconda.org/conda-forge/river) (π₯ 91K Β· β±οΈ 06.10.2023):
```
conda install -c conda-forge river
```
</details>
<details><summary><b><a href="https://github.com/PaddlePaddle/PaddleHub">PaddleHub</a></b> (π₯31 Β· β 13K) - Awesome pre-trained models toolkit based on PaddlePaddle... <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/PaddlePaddle/PaddleHub) (π¨βπ» 70 Β· π 2.1K Β· π₯ 840 Β· π¦ 1.8K Β· π 1.3K - 44% open Β· β±οΈ 07.08.2024):
```
git clone https://github.com/PaddlePaddle/PaddleHub
```
- [PyPi](https://pypi.org/project/paddlehub) (π₯ 5.6K / month Β· π¦ 7 Β· β±οΈ 20.09.2023):
```
pip install paddlehub
```
</details>
<details><summary><b><a href="https://github.com/tensorly/tensorly">tensorly</a></b> (π₯31 Β· β 1.6K Β· π) - TensorLy: Tensor Learning in Python. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
- [GitHub](https://github.com/tensorly/tensorly) (π¨βπ» 69 Β· π 290 Β· π 270 - 21% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/tensorly/tensorly
```
- [PyPi](https://pypi.org/project/tensorly) (π₯ 170K / month Β· π¦ 99 Β· β±οΈ 12.11.2024):
```
pip install tensorly
```
- [Conda](https://anaconda.org/conda-forge/tensorly) (π₯ 370K Β· β±οΈ 10.06.2024):
```
conda install -c conda-forge tensorly
```
</details>
<details><summary><b><a href="https://github.com/pyjanitor-devs/pyjanitor">pyjanitor</a></b> (π₯31 Β· β 1.4K) - Clean APIs for data cleaning. Python implementation of R package.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/pyjanitor-devs/pyjanitor) (π¨βπ» 110 Β· π 170 Β· π¦ 780 Β· π 570 - 19% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/pyjanitor-devs/pyjanitor
```
- [PyPi](https://pypi.org/project/pyjanitor) (π₯ 93K / month Β· π¦ 36 Β· β±οΈ 04.12.2024):
```
pip install pyjanitor
```
- [Conda](https://anaconda.org/conda-forge/pyjanitor) (π₯ 230K Β· β±οΈ 05.12.2024):
```
conda install -c conda-forge pyjanitor
```
</details>
<details><summary><b><a href="https://github.com/inducer/pyopencl">pyopencl</a></b> (π₯31 Β· β 1.1K) - OpenCL integration for Python, plus shiny features. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/inducer/pyopencl) (π¨βπ» 96 Β· π 240 Β· π¦ 2.1K Β· π 360 - 21% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/inducer/pyopencl
```
- [PyPi](https://pypi.org/project/pyopencl) (π₯ 81K / month Β· π¦ 170 Β· β±οΈ 18.10.2024):
```
pip install pyopencl
```
- [Conda](https://anaconda.org/conda-forge/pyopencl) (π₯ 1.4M Β· β±οΈ 22.10.2024):
```
conda install -c conda-forge pyopencl
```
</details>
<details><summary><b><a href="https://github.com/uber/causalml">causalml</a></b> (π₯30 Β· β 5.1K) - Uplift modeling and causal inference with machine learning.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/uber/causalml) (π¨βπ» 64 Β· π 780 Β· π¦ 240 Β· π 400 - 13% open Β· β±οΈ 13.12.2024):
```
git clone https://github.com/uber/causalml
```
- [PyPi](https://pypi.org/project/causalml) (π₯ 36K / month Β· π¦ 2 Β· β±οΈ 01.10.2024):
```
pip install causalml
```
</details>
<details><summary><b><a href="https://github.com/dstackai/dstack">dstack</a></b> (π₯30 Β· β 1.6K) - dstack is a lightweight, open-source alternative to Kubernetes &.. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code></summary>
- [GitHub](https://github.com/dstackai/dstack) (π¨βπ» 49 Β· π 160 Β· π¦ 17 Β· π 1.1K - 9% open Β· β±οΈ 19.12.2024):
```
git clone https://github.com/dstackai/dstack
```
- [PyPi](https://pypi.org/project/dstack) (π₯ 8.2K / month Β· β±οΈ 18.12.2024):
```
pip install dstack
```
</details>
<details><summary><b><a href="https://github.com/openvinotoolkit/anomalib">anomalib</a></b> (π₯29 Β· β 3.9K) - An anomaly detection library comprising state-of-the-art algorithms.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/openvinotoolkit/anomalib) (π¨βπ» 81 Β· π 680 Β· π₯ 16K Β· π¦ 120 Β· π 950 - 15% open Β· β±οΈ 05.11.2024):
```
git clone https://github.com/openvinotoolkit/anomalib
```
- [PyPi](https://pypi.org/project/anomalib) (π₯ 31K / month Β· π¦ 5 Β· β±οΈ 31.10.2024):
```
pip install anomalib
```
</details>
<details><summary><b><a href="https://github.com/ContinualAI/avalanche">avalanche</a></b> (π₯29 Β· β 1.8K) - Avalanche: an End-to-End Library for Continual Learning based on.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/ContinualAI/avalanche) (π¨βπ» 80 Β· π 290 Β· π₯ 43 Β· π¦ 110 Β· π 820 - 12% open Β· β±οΈ 29.10.2024):
```
git clone https://github.com/ContinualAI/avalanche
```
- [PyPi](https://pypi.org/project/avalanche-lib) (π₯ 1.5K / month Β· π¦ 3 Β· β±οΈ 29.10.2024):
```
pip install avalanche-lib
```
</details>
<details><summary><b><a href="https://github.com/tableau/TabPy">TabPy</a></b> (π₯29 Β· β 1.6K) - Execute Python code on the fly and display results in Tableau visualizations:. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/tableau/TabPy) (π¨βπ» 51 Β· π 600 Β· π¦ 190 Β· π 320 - 6% open Β· β±οΈ 25.11.2024):
```
git clone https://github.com/tableau/TabPy
```
- [PyPi](https://pypi.org/project/tabpy) (π₯ 8K / month Β· π¦ 2 Β· β±οΈ 25.11.2024):
```
pip install tabpy
```
- [Conda](https://anaconda.org/anaconda/tabpy-client) (π₯ 4.8K Β· β±οΈ 16.06.2023):
```
conda install -c anaconda tabpy-client
```
</details>
<details><summary><b><a href="https://github.com/google/trax">Trax</a></b> (π₯28 Β· β 8.1K) - Trax Deep Learning with Clear Code and Speed. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/google/trax) (π¨βπ» 80 Β· π 810 Β· π¦ 200 Β· π 250 - 49% open Β· β±οΈ 10.09.2024):
```
git clone https://github.com/google/trax
```
- [PyPi](https://pypi.org/project/trax) (π₯ 4.1K / month Β· π¦ 1 Β· β±οΈ 26.10.2021):
```
pip install trax
```
</details>
<details><summary><b><a href="https://github.com/MaxHalford/prince">Prince</a></b> (π₯28 Β· β 1.3K) - Multivariate exploratory data analysis in Python PCA, CA, MCA, MFA,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/MaxHalford/prince) (π¨βπ» 16 Β· π 180 Β· π¦ 640 Β· π 130 - 0% open Β· β±οΈ 17.11.2024):
```
git clone https://github.com/MaxHalford/prince
```
- [PyPi](https://pypi.org/project/prince) (π₯ 140K / month Β· π¦ 18 Β· β±οΈ 17.11.2024):
```
pip install prince
```
- [Conda](https://anaconda.org/conda-forge/prince-factor-analysis) (π₯ 22K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge prince-factor-analysis
```
</details>
<details><summary><b><a href="https://github.com/nicodv/kmodes">kmodes</a></b> (π₯28 Β· β 1.2K Β· π€) - Python implementations of the k-modes and k-prototypes clustering.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/nicodv/kmodes) (π¨βπ» 22 Β· π 420 Β· π¦ 2.9K Β· π 160 - 10% open Β· β±οΈ 17.01.2024):
```
git clone https://github.com/nicodv/kmodes
```
- [PyPi](https://pypi.org/project/kmodes) (π₯ 220K / month Β· π¦ 38 Β· β±οΈ 06.09.2022):
```
pip install kmodes
```
- [Conda](https://anaconda.org/conda-forge/kmodes) (π₯ 52K Β· β±οΈ 16.06.2023):
```
conda install -c conda-forge kmodes
```
</details>
<details><summary><b><a href="https://github.com/annoviko/pyclustering">pyclustering</a></b> (π₯28 Β· β 1.2K Β· π€) - pyclustering is a Python, C++ data mining library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/annoviko/pyclustering) (π¨βπ» 26 Β· π 250 Β· π₯ 650 Β· π¦ 780 Β· π 670 - 11% open Β· β±οΈ 08.02.2024):
```
git clone https://github.com/annoviko/pyclustering
```
- [PyPi](https://pypi.org/project/pyclustering) (π₯ 31K / month Β· π¦ 32 Β· β±οΈ 25.11.2020):
```
pip install pyclustering
```
- [Conda](https://anaconda.org/conda-forge/pyclustering) (π₯ 99K Β· β±οΈ 08.11.2024):
```
conda install -c conda-forge pyclustering
```
</details>
<details><summary><b><a href="https://github.com/sepandhaghighi/pycm">pycm</a></b> (π₯27 Β· β 1.5K) - Multi-class confusion matrix library in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/sepandhaghighi/pycm) (π¨βπ» 17 Β· π 120 Β· π¦ 360 Β· π 210 - 7% open Β· β±οΈ 15.10.2024):
```
git clone https://github.com/sepandhaghighi/pycm
```
- [PyPi](https://pypi.org/project/pycm) (π₯ 44K / month Β· π¦ 24 Β· β±οΈ 17.10.2024):
```
pip install pycm
```
</details>
<details><summary><b><a href="https://github.com/adapter-hub/adapters">adapter-transformers</a></b> (π₯26 Β· β 2.6K) - A Unified Library for Parameter-Efficient and Modular.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code>huggingface</code></summary>
- [GitHub](https://github.com/adapter-hub/adapters) (π¨βπ» 14 Β· π 350 Β· π¦ 140 Β· π 390 - 11% open Β· β±οΈ 02.12.2024):
```
git clone https://github.com/Adapter-Hub/adapter-transformers
```
- [PyPi](https://pypi.org/project/adapter-transformers) (π₯ 4.4K / month Β· π¦ 12 Β· β±οΈ 07.07.2024):
```
pip install adapter-transformers
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/AugLy">AugLy</a></b> (π₯25 Β· β 5K) - A data augmentations library for audio, image, text, and video. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/facebookresearch/AugLy) (π¨βπ» 38 Β· π 300 Β· π¦ 160 Β· π 78 - 30% open Β· β±οΈ 21.11.2024):
```
git clone https://github.com/facebookresearch/AugLy
```
- [PyPi](https://pypi.org/project/augly) (π₯ 3K / month Β· π¦ 4 Β· β±οΈ 05.12.2023):
```
pip install augly
```
</details>
<details><summary><b><a href="https://github.com/solegalli/feature_engine">Feature Engine</a></b> (π₯25 Β· β 1.9K) - Feature engineering package with sklearn like functionality. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary>
- [GitHub](https://github.com/solegalli/feature_engine) (π¨βπ» 49 Β· π 310 Β· β±οΈ 31.08.2024):
```
git clone https://github.com/solegalli/feature_engine
```
- [PyPi](https://pypi.org/project/feature_engine) (π₯ 240K / month Β· π¦ 170 Β· β±οΈ 03.11.2024):
```
pip install feature_engine
```
- [Conda](https://anaconda.org/conda-forge/feature_engine) (π₯ 62K Β· β±οΈ 01.09.2024):
```
conda install -c conda-forge feature_engine
```
</details>
<details><summary><b><a href="https://github.com/scikit-learn-contrib/metric-learn">metric-learn</a></b> (π₯25 Β· β 1.4K) - Metric learning algorithms in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/scikit-learn-contrib/metric-learn) (π¨βπ» 23 Β· π 230 Β· π¦ 430 Β· π 170 - 30% open Β· β±οΈ 03.08.2024):
```
git clone https://github.com/scikit-learn-contrib/metric-learn
```
- [PyPi](https://pypi.org/project/metric-learn) (π₯ 5.7K / month Β· π¦ 7 Β· β±οΈ 09.10.2023):
```
pip install metric-learn
```
- [Conda](https://anaconda.org/conda-forge/metric-learn) (π₯ 14K Β· β±οΈ 09.10.2023):
```
conda install -c conda-forge metric-learn
```
</details>
<details><summary><b><a href="https://github.com/Project-MONAI/MONAILabel">MONAILabel</a></b> (π₯24 Β· β 630) - MONAI Label is an intelligent open source image labeling and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary>
- [GitHub](https://github.com/Project-MONAI/MONAILabel) (π¨βπ» 65 Β· π 200 Β· π₯ 110K Β· π 530 - 24% open Β· β±οΈ 16.12.2024):
```
git clone https://github.com/Project-MONAI/MONAILabel
```
- [PyPi](https://pypi.org/project/monailabel-weekly) (π₯ 2.1K / month Β· β±οΈ 01.10.2023):
```
pip install monailabel-weekly
```
</details>
<details><summary><b><a href="https://github.com/astroML/astroML">AstroML</a></b> (π₯23 Β· β 1.1K Β· π€) - Machine learning, statistics, and data mining for astronomy.. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/astroML/astroML) (π¨βπ» 31 Β· π 300 Β· π 160 - 38% open Β· β±οΈ 04.01.2024):
```
git clone https://github.com/astroML/astroML
```
- [PyPi](https://pypi.org/project/astroML) (π₯ 1.8K / month Β· π¦ 16 Β· β±οΈ 01.03.2022):
```
pip install astroML
```
- [Conda](https://anaconda.org/conda-forge/astroml) (π₯ 50K Β· β±οΈ 27.11.2024):
```
conda install -c conda-forge astroml
```
</details>
<details><summary><b><a href="https://github.com/BioPandas/biopandas">BioPandas</a></b> (π₯23 Β· β 720) - Working with molecular structures in pandas DataFrames. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/BioPandas/biopandas) (π¨βπ» 18 Β· π 120 Β· π¦ 320 Β· π 59 - 35% open Β· β±οΈ 01.08.2024):
```
git clone https://github.com/rasbt/biopandas
```
- [PyPi](https://pypi.org/project/biopandas) (π₯ 9.6K / month Β· π¦ 38 Β· β±οΈ 01.08.2024):
```
pip install biopandas
```
- [Conda](https://anaconda.org/conda-forge/biopandas) (π₯ 170K Β· β±οΈ 02.08.2024):
```
conda install -c conda-forge biopandas
```
</details>
<details><summary><b><a href="https://github.com/clementchadebec/benchmark_VAE">benchmark_VAE</a></b> (π₯21 Β· β 1.8K) - Unifying Variational Autoencoder (VAE) implementations.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/clementchadebec/benchmark_VAE) (π¨βπ» 18 Β· π 160 Β· π¦ 37 Β· π 69 - 37% open Β· β±οΈ 17.07.2024):
```
git clone https://github.com/clementchadebec/benchmark_VAE
```
- [PyPi](https://pypi.org/project/pythae) (π₯ 1.3K / month Β· β±οΈ 06.09.2023):
```
pip install pythae
```
</details>
<details><summary><b><a href="https://github.com/yzhao062/SUOD">SUOD</a></b> (π₯21 Β· β 380 Β· π€) - (MLSys 21) An Acceleration System for Large-scare Unsupervised.. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary>
- [GitHub](https://github.com/yzhao062/SUOD) (π¨βπ» 3 Β· π 49 Β· π¦ 540 Β· π 15 - 80% open Β· β±οΈ 08.02.2024):
```
git clone https://github.com/yzhao062/SUOD
```
- [PyPi](https://pypi.org/project/suod) (π₯ 48K / month Β· π¦ 8 Β· β±οΈ 08.02.2024):
```
pip install suod
```
</details>
<details><summary><b><a href="https://github.com/infer-actively/pymdp">pymdp</a></b> (π₯20 Β· β 480) - A Python implementation of active inference for Markov Decision Processes. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/infer-actively/pymdp) (π¨βπ» 18 Β· π 94 Β· π¦ 14 Β· π 45 - 40% open Β· β±οΈ 26.11.2024):
```
git clone https://github.com/infer-actively/pymdp
```
- [PyPi](https://pypi.org/project/inferactively-pymdp) (π₯ 9K / month Β· β±οΈ 08.12.2022):
```
pip install inferactively-pymdp
```
</details>
<details><summary><b><a href="https://github.com/pykale/pykale">pykale</a></b> (π₯19 Β· β 440) - Knowledge-Aware machine LEarning (KALE): accessible machine learning.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code></summary>
- [GitHub](https://github.com/pykale/pykale) (π¨βπ» 25 Β· π 64 Β· π¦ 5 Β· π 120 - 8% open Β· β±οΈ 24.09.2024):
```
git clone https://github.com/pykale/pykale
```
- [PyPi](https://pypi.org/project/pykale) (π₯ 230 / month Β· β±οΈ 12.04.2022):
```
pip install pykale
```
</details>
<details><summary><b><a href="https://github.com/facebookresearch/NeuralCompression">NeuralCompression</a></b> (π₯16 Β· β 520) - A collection of tools for neural compression enthusiasts. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary>
- [GitHub](https://github.com/facebookresearch/NeuralCompression) (π¨βπ» 10 Β· π 42 Β· π 71 - 8% open Β· β±οΈ 20.09.2024):
```
git clone https://github.com/facebookresearch/NeuralCompression
```
- [PyPi](https://pypi.org/project/neuralcompression) (π₯ 150 / month Β· β±οΈ 03.10.2023):
```
pip install neuralcompression
```
</details>
<details><summary>Show 25 hidden projects...</summary>
- <b><a href="https://github.com/explosion/cython-blis">Cython BLIS</a></b> (π₯31 Β· β 220) - Fast matrix-multiplication as a self-contained Python library no.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/cleanlab/cleanlab">cleanlab</a></b> (π₯30 Β· β 9.8K) - The standard data-centric AI package for data quality and machine.. <code><a href="http://bit.ly/3pwmjO5">βοΈAGPL-3.0</a></code>
- <b><a href="https://github.com/SeldonIO/alibi-detect">alibi-detect</a></b> (π₯29 Β· β 2.3K) - Algorithms for outlier, adversarial and drift detection. <code><a href="https://tldrlegal.com/search?q=Intel">βοΈIntel</a></code>
- <b><a href="https://github.com/google-deepmind/pysc2">pysc2</a></b> (π₯28 Β· β 8K Β· π) - StarCraft II Learning Environment. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/modAL-python/modAL">modAL</a></b> (π₯28 Β· β 2.2K Β· π) - A modular active learning framework for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/JustGlowing/minisom">minisom</a></b> (π₯27 Β· β 1.5K) - MiniSom is a minimalistic implementation of the Self Organizing.. <code><a href="https://tldrlegal.com/search?q=CC-BY-3.0">βοΈCC-BY-3.0</a></code>
- <b><a href="https://github.com/ljvmiranda921/pyswarms">PySwarms</a></b> (π₯27 Β· β 1.3K Β· π) - A research toolkit for particle swarm optimization in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/trevorstephens/gplearn">gplearn</a></b> (π₯26 Β· β 1.6K Β· π) - Genetic Programming in Python, with a scikit-learn inspired API. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/dbt-labs/metricflow">metricflow</a></b> (π₯25 Β· β 1.2K) - MetricFlow allows you to define, build, and maintain metrics.. <code>βUnlicensed</code>
- <b><a href="https://github.com/mars-project/mars">Mars</a></b> (π₯24 Β· β 2.7K Β· π) - Mars is a tensor-based unified framework for large-scale data.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/minrk/findspark">findspark</a></b> (π₯24 Β· β 510 Β· π) - Find pyspark to make it importable. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/Sinaptik-AI/pandas-ai">pandas-ai</a></b> (π₯22 Β· β 14K) - Chat with your database (SQL, CSV, pandas, polars, mongodb,.. <code>βUnlicensed</code>
- <b><a href="https://github.com/ml-tooling/opyrator">opyrator</a></b> (π₯22 Β· β 3.1K Β· π) - Turns your machine learning code into microservices with web API,.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/flennerhag/mlens">mlens</a></b> (π₯22 Β· β 850 Β· π) - ML-Ensemble high performance ensemble learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/vecxoz/vecstack">vecstack</a></b> (π₯22 Β· β 690 Β· π) - Python package for stacking (machine learning technique). <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/eltonlaw/impyute">impyute</a></b> (π₯21 Β· β 360 Β· π) - Data imputations library to preprocess datasets with missing data. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/airbnb/streamalert">StreamAlert</a></b> (π₯20 Β· β 2.9K Β· π) - StreamAlert is a serverless, realtime data analysis.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code>
- <b><a href="https://github.com/kLabUM/rrcf">rrcf</a></b> (π₯20 Β· β 500 Β· π) - Implementation of the Robust Random Cut Forest algorithm for anomaly.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/jmschrei/apricot">apricot</a></b> (π₯20 Β· β 500 Β· π) - apricot implements submodular optimization for the purpose of.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/alegonz/baikal">baikal</a></b> (π₯19 Β· β 590 Β· π) - A graph-based functional API for building complex scikit-learn.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code>
- <b><a href="https://github.com/EpistasisLab/scikit-rebate">scikit-rebate</a></b> (π₯19 Β· β 420 Β· π) - A scikit-learn-compatible Python implementation of.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/SforAiDl/KD_Lib">KD-Lib</a></b> (π₯16 Β· β 610 Β· π) - A Pytorch Knowledge Distillation library for benchmarking and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/pandas-ml/pandas-ml">pandas-ml</a></b> (π₯16 Β· β 320 Β· π) - pandas, scikit-learn, xgboost and seaborn integration. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> <code><img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13"></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code>
- <b><a href="https://github.com/jrieke/traingenerator">traingenerator</a></b> (π₯13 Β· β 1.4K Β· π) - A web app to generate template code for machine learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
- <b><a href="https://github.com/Palashio/nylon">nylon</a></b> (π₯13 Β· β 83 Β· π) - An intelligent, flexible grammar of machine learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code>
</details>
---
## Related Resources
- [**Papers With Code**](https://paperswithcode.com): Discover ML papers, code, and evaluation tables.
- [**Sotabench**](https://sotabench.com): Discover & compare open-source ML models.
- [**Google Dataset Search**](https://toolbox.google.com/datasetsearch): Dataset search engine by Google.
- [**Dataset List**](https://www.datasetlist.com/): List of the biggest ML datasets from across the web.
- [**Awesome Public Datasets**](https://github.com/awesomedata/awesome-public-datasets): A topic-centric list of open datasets.
- [**Best-of lists**](https://best-of.org): Discover other best-of lists with awesome open-source projects on all kinds of topics.
- [**best-of-python-dev**](https://github.com/ml-tooling/best-of-python-dev): A ranked list of awesome python developer tools and libraries.
- [**best-of-web-python**](https://github.com/ml-tooling/best-of-web-python): A ranked list of awesome python libraries for web development.
## Contribution
Contributions are encouraged and always welcome! If you like to add or update projects, choose one of the following ways:
- Open an issue by selecting one of the provided categories from the [issue page](https://github.com/ml-tooling/best-of-ml-python/issues/new/choose) and fill in the requested information.
- Modify the [projects.yaml](https://github.com/ml-tooling/best-of-ml-python/blob/main/projects.yaml) with your additions or changes, and submit a pull request. This can also be done directly via the [Github UI](https://github.com/ml-tooling/best-of-ml-python/edit/main/projects.yaml).
If you like to contribute to or share suggestions regarding the project metadata collection or markdown generation, please refer to the [best-of-generator](https://github.com/best-of-lists/best-of-generator) repository. If you like to create your own best-of list, we recommend to follow [this guide](https://github.com/best-of-lists/best-of/blob/main/create-best-of-list.md).
For more information on how to add or update projects, please read the [contribution guidelines](https://github.com/ml-tooling/best-of-ml-python/blob/main/CONTRIBUTING.md). By participating in this project, you agree to abide by its [Code of Conduct](https://github.com/ml-tooling/best-of-ml-python/blob/main/.github/CODE_OF_CONDUCT.md).
## License
[![CC0](https://mirrors.creativecommons.org/presskit/buttons/88x31/svg/by-sa.svg)](https://creativecommons.org/licenses/by-sa/4.0/)
", Assign "at most 3 tags" to the expected json: {"id":"12155","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"