base on 🏆 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>🏆&nbsp; 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> <a href="https://mltooling.substack.com/subscribe" title="Subscribe to newsletter"><img src="http://bit.ly/2Md9rxM"></a> <a href="https://twitter.com/mltooling" title="Follow on Twitter"><img src="https://img.shields.io/twitter/follow/mltooling.svg?style=social&label=Follow"></a> </p> This curated list contains 920 awesome open-source projects with a total of 4.9M 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"> 🧙‍♂️&nbsp; 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> 📫&nbsp; Subscribe to our <a href="https://mltooling.substack.com/subscribe">newsletter</a> for updates and trending projects. </p> --- ## 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) _2 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) _55 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 - 🥇🥈🥉&nbsp; Combined project-quality score - ⭐️&nbsp; Star count from GitHub - 🐣&nbsp; New project _(less than 6 months old)_ - 💤&nbsp; Inactive project _(6 months no activity)_ - 💀&nbsp; Dead project _(12 months no activity)_ - 📈📉&nbsp; Project is trending up or down - ➕&nbsp; Project was recently added - ❗️&nbsp; Warning _(e.g. missing/risky license)_ - 👨‍💻&nbsp; Contributors count from GitHub - 🔀&nbsp; Fork count from GitHub - 📋&nbsp; Issue count from GitHub - ⏱️&nbsp; Last update timestamp on package manager - 📥&nbsp; Download count from package manager - 📦&nbsp; Number of dependent projects - <img src="https://git.io/JLy1A" style="display:inline;" width="13" height="13">&nbsp; Tensorflow related project - <img src="https://git.io/JLy1F" style="display:inline;" width="13" height="13">&nbsp; Sklearn related project - <img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13">&nbsp; PyTorch related project - <img src="https://git.io/JLy1X" style="display:inline;" width="13" height="13">&nbsp; MxNet related project - <img src="https://git.io/JLy1N" style="display:inline;" width="13" height="13">&nbsp; Apache Spark related project - <img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13">&nbsp; Jupyter related project - <img src="https://git.io/JLy1M" style="display:inline;" width="13" height="13">&nbsp; PaddlePaddle related project - <img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13">&nbsp; Pandas related project - <img src="https://jax.readthedocs.io/en/latest/_static/favicon.png" style="display:inline;" width="13" height="13">&nbsp; 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> (🥇56 · ⭐ 190K) - 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) (👨‍💻 4.8K · 🔀 75K · 📦 500K · 📋 47K - 15% open · ⏱️ 24.04.2025): ``` git clone https://github.com/tensorflow/tensorflow ``` - [PyPi](https://pypi.org/project/tensorflow) (📥 22M / month · 📦 8.7K · ⏱️ 12.03.2025): ``` pip install tensorflow ``` - [Conda](https://anaconda.org/conda-forge/tensorflow) (📥 5.5M · ⏱️ 22.04.2025): ``` conda install -c conda-forge tensorflow ``` - [Docker Hub](https://hub.docker.com/r/tensorflow/tensorflow) (📥 80M · ⭐ 2.7K · ⏱️ 24.04.2025): ``` docker pull tensorflow/tensorflow ``` </details> <details><summary><b><a href="https://github.com/pytorch/pytorch">PyTorch</a></b> (🥇55 · ⭐ 89K) - 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) (👨‍💻 5.6K · 🔀 24K · 📥 85K · 📦 730K · 📋 52K - 31% open · ⏱️ 24.04.2025): ``` git clone https://github.com/pytorch/pytorch ``` - [PyPi](https://pypi.org/project/torch) (📥 48M / month · 📦 24K · ⏱️ 23.04.2025): ``` pip install torch ``` - [Conda](https://anaconda.org/pytorch/pytorch) (📥 27M · ⏱️ 25.03.2025): ``` conda install -c pytorch pytorch ``` </details> <details><summary><b><a href="https://github.com/scikit-learn/scikit-learn">scikit-learn</a></b> (🥇53 · ⭐ 62K) - 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) (👨‍💻 3.3K · 🔀 26K · 📥 1.1K · 📦 1.2M · 📋 12K - 17% open · ⏱️ 24.04.2025): ``` git clone https://github.com/scikit-learn/scikit-learn ``` - [PyPi](https://pypi.org/project/scikit-learn) (📥 93M / month · 📦 30K · ⏱️ 10.01.2025): ``` pip install scikit-learn ``` - [Conda](https://anaconda.org/conda-forge/scikit-learn) (📥 36M · ⏱️ 22.04.2025): ``` conda install -c conda-forge scikit-learn ``` </details> <details><summary><b><a href="https://github.com/keras-team/keras">Keras</a></b> (🥇47 · ⭐ 63K) - 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) (👨‍💻 1.4K · 🔀 20K · 📋 12K - 2% open · ⏱️ 23.04.2025): ``` git clone https://github.com/keras-team/keras ``` - [PyPi](https://pypi.org/project/keras) (📥 15M / month · 📦 1.8K · ⏱️ 02.04.2025): ``` pip install keras ``` - [Conda](https://anaconda.org/conda-forge/keras) (📥 4.1M · ⏱️ 22.04.2025): ``` conda install -c conda-forge keras ``` </details> <details><summary><b><a href="https://github.com/dmlc/xgboost">XGBoost</a></b> (🥇46 · ⭐ 27K) - 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) (👨‍💻 660 · 🔀 8.8K · 📥 16K · 📦 150K · 📋 5.5K - 8% open · ⏱️ 23.04.2025): ``` git clone https://github.com/dmlc/xgboost ``` - [PyPi](https://pypi.org/project/xgboost) (📥 25M / month · 📦 2.3K · ⏱️ 15.03.2025): ``` pip install xgboost ``` - [Conda](https://anaconda.org/conda-forge/xgboost) (📥 6M · ⏱️ 22.04.2025): ``` conda install -c conda-forge xgboost ``` </details> <details><summary><b><a href="https://github.com/jax-ml/jax">jax</a></b> (🥇45 · ⭐ 32K) - 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) (👨‍💻 860 · 🔀 3K · 📦 42K · 📋 6.1K - 24% open · ⏱️ 24.04.2025): ``` git clone https://github.com/google/jax ``` - [PyPi](https://pypi.org/project/jax) (📥 8.4M / month · 📦 2.4K · ⏱️ 17.04.2025): ``` pip install jax ``` - [Conda](https://anaconda.org/conda-forge/jaxlib) (📥 2.5M · ⏱️ 22.04.2025): ``` conda install -c conda-forge jaxlib ``` </details> <details><summary><b><a href="https://github.com/PaddlePaddle/Paddle">PaddlePaddle</a></b> (🥇45 · ⭐ 23K) - 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) (👨‍💻 1.4K · 🔀 5.7K · 📥 15K · 📦 7.8K · 📋 19K - 9% open · ⏱️ 24.04.2025): ``` git clone https://github.com/PaddlePaddle/Paddle ``` - [PyPi](https://pypi.org/project/paddlepaddle) (📥 400K / month · 📦 230 · ⏱️ 26.03.2025): ``` pip install paddlepaddle ``` </details> <details><summary><b><a href="https://github.com/apache/spark">PySpark</a></b> (🥈44 · ⭐ 41K · 📉) - 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) (👨‍💻 3.2K · 🔀 28K · ⏱️ 24.04.2025): ``` git clone https://github.com/apache/spark ``` - [PyPi](https://pypi.org/project/pyspark) (📥 42M / month · 📦 1.8K · ⏱️ 27.02.2025): ``` pip install pyspark ``` - [Conda](https://anaconda.org/conda-forge/pyspark) (📥 3.8M · ⏱️ 22.04.2025): ``` conda install -c conda-forge pyspark ``` </details> <details><summary><b><a href="https://github.com/Lightning-AI/pytorch-lightning">pytorch-lightning</a></b> (🥈44 · ⭐ 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) (👨‍💻 1K · 🔀 3.5K · 📥 12K · 📦 45K · 📋 7.3K - 12% open · ⏱️ 24.04.2025): ``` git clone https://github.com/Lightning-AI/lightning ``` - [PyPi](https://pypi.org/project/pytorch-lightning) (📥 8.3M / month · 📦 1.6K · ⏱️ 19.03.2025): ``` pip install pytorch-lightning ``` - [Conda](https://anaconda.org/conda-forge/pytorch-lightning) (📥 1.5M · ⏱️ 22.04.2025): ``` conda install -c conda-forge pytorch-lightning ``` </details> <details><summary><b><a href="https://github.com/statsmodels/statsmodels">StatsModels</a></b> (🥈44 · ⭐ 11K) - 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) (👨‍💻 450 · 🔀 3.1K · 📥 35 · 📦 170K · 📋 5.7K - 50% open · ⏱️ 02.04.2025): ``` git clone https://github.com/statsmodels/statsmodels ``` - [PyPi](https://pypi.org/project/statsmodels) (📥 17M / month · 📦 4.5K · ⏱️ 03.10.2024): ``` pip install statsmodels ``` - [Conda](https://anaconda.org/conda-forge/statsmodels) (📥 19M · ⏱️ 22.04.2025): ``` conda install -c conda-forge statsmodels ``` </details> <details><summary><b><a href="https://github.com/fastai/fastai">Fastai</a></b> (🥈42 · ⭐ 27K · 📈) - 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) (👨‍💻 670 · 🔀 7.6K · 📦 22K · 📋 1.8K - 13% open · ⏱️ 19.04.2025): ``` git clone https://github.com/fastai/fastai ``` - [PyPi](https://pypi.org/project/fastai) (📥 500K / month · 📦 330 · ⏱️ 18.04.2025): ``` pip install fastai ``` </details> <details><summary><b><a href="https://github.com/microsoft/LightGBM">LightGBM</a></b> (🥈42 · ⭐ 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) (👨‍💻 330 · 🔀 3.9K · 📥 290K · 📦 50K · 📋 3.5K - 11% open · ⏱️ 24.04.2025): ``` git clone https://github.com/microsoft/LightGBM ``` - [PyPi](https://pypi.org/project/lightgbm) (📥 10M / month · 📦 1.2K · ⏱️ 15.02.2025): ``` pip install lightgbm ``` - [Conda](https://anaconda.org/conda-forge/lightgbm) (📥 3.4M · ⏱️ 22.04.2025): ``` conda install -c conda-forge lightgbm ``` </details> <details><summary><b><a href="https://github.com/catboost/catboost">Catboost</a></b> (🥈42 · ⭐ 8.4K) - 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) (👨‍💻 1.3K · 🔀 1.2K · 📥 380K · 📦 16 · 📋 2.4K - 25% open · ⏱️ 24.04.2025): ``` git clone https://github.com/catboost/catboost ``` - [PyPi](https://pypi.org/project/catboost) (📥 2.9M / month · 📦 650 · ⏱️ 13.04.2025): ``` pip install catboost ``` - [Conda](https://anaconda.org/conda-forge/catboost) (📥 2M · ⏱️ 22.04.2025): ``` conda install -c conda-forge catboost ``` </details> <details><summary><b><a href="https://github.com/apache/flink">PyFlink</a></b> (🥈40 · ⭐ 25K) - Apache Flink Python API. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/apache/flink) (👨‍💻 2K · 🔀 13K · 📦 21 · ⏱️ 24.04.2025): ``` git clone https://github.com/apache/flink ``` - [PyPi](https://pypi.org/project/apache-flink) (📥 5.5M / month · 📦 35 · ⏱️ 12.02.2025): ``` pip install apache-flink ``` </details> <details><summary><b><a href="https://github.com/google/flax">Flax</a></b> (🥈37 · ⭐ 6.5K) - 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) (👨‍💻 260 · 🔀 690 · 📥 60 · 📦 14K · 📋 1.2K - 33% open · ⏱️ 23.04.2025): ``` git clone https://github.com/google/flax ``` - [PyPi](https://pypi.org/project/flax) (📥 1.6M / month · 📦 610 · ⏱️ 23.04.2025): ``` pip install flax ``` - [Conda](https://anaconda.org/conda-forge/flax) (📥 97K · ⏱️ 22.04.2025): ``` conda install -c conda-forge flax ``` </details> <details><summary><b><a href="https://github.com/pytorch/ignite">Ignite</a></b> (🥈37 · ⭐ 4.7K) - 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) (👨‍💻 840 · 🔀 650 · 📦 3.7K · 📋 1.4K - 11% open · ⏱️ 24.04.2025): ``` git clone https://github.com/pytorch/ignite ``` - [PyPi](https://pypi.org/project/pytorch-ignite) (📥 180K / month · 📦 110 · ⏱️ 24.04.2025): ``` pip install pytorch-ignite ``` - [Conda](https://anaconda.org/pytorch/ignite) (📥 230K · ⏱️ 30.03.2025): ``` conda install -c pytorch ignite ``` </details> <details><summary><b><a href="https://github.com/arogozhnikov/einops">einops</a></b> (🥈36 · ⭐ 8.9K) - 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) (👨‍💻 33 · 🔀 360 · 📦 71K · 📋 200 - 18% open · ⏱️ 09.02.2025): ``` git clone https://github.com/arogozhnikov/einops ``` - [PyPi](https://pypi.org/project/einops) (📥 9.4M / month · 📦 2.6K · ⏱️ 09.02.2025): ``` pip install einops ``` - [Conda](https://anaconda.org/conda-forge/einops) (📥 370K · ⏱️ 22.04.2025): ``` conda install -c conda-forge einops ``` </details> <details><summary><b><a href="https://github.com/jina-ai/serve">Jina</a></b> (🥈35 · ⭐ 22K) - 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) (👨‍💻 180 · 🔀 2.2K · 📋 1.9K - 0% open · ⏱️ 24.03.2025): ``` git clone https://github.com/jina-ai/jina ``` - [PyPi](https://pypi.org/project/jina) (📥 85K / month · 📦 29 · ⏱️ 24.03.2025): ``` pip install jina ``` - [Conda](https://anaconda.org/conda-forge/jina-core) (📥 92K · ⏱️ 22.04.2025): ``` conda install -c conda-forge jina-core ``` - [Docker Hub](https://hub.docker.com/r/jinaai/jina) (📥 1.8M · ⭐ 8 · ⏱️ 24.03.2025): ``` docker pull jinaai/jina ``` </details> <details><summary><b><a href="https://github.com/ivy-llc/ivy">ivy</a></b> (🥈34 · ⭐ 14K) - Convert Machine Learning Code Between Frameworks. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/ivy-llc/ivy) (👨‍💻 1.5K · 🔀 5.7K · 📋 17K - 5% open · ⏱️ 19.04.2025): ``` git clone https://github.com/unifyai/ivy ``` - [PyPi](https://pypi.org/project/ivy) (📥 29K / month · 📦 16 · ⏱️ 21.02.2025): ``` pip install ivy ``` </details> <details><summary><b><a href="https://github.com/explosion/thinc">Thinc</a></b> (🥈34 · ⭐ 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) (👨‍💻 67 · 🔀 280 · 📥 1.2K · 📦 66K · 📋 150 - 12% open · ⏱️ 07.03.2025): ``` git clone https://github.com/explosion/thinc ``` - [PyPi](https://pypi.org/project/thinc) (📥 17M / month · 📦 160 · ⏱️ 04.04.2025): ``` pip install thinc ``` - [Conda](https://anaconda.org/conda-forge/thinc) (📥 3.5M · ⏱️ 22.04.2025): ``` conda install -c conda-forge thinc ``` </details> <details><summary><b><a href="https://github.com/VowpalWabbit/vowpal_wabbit">Vowpal Wabbit</a></b> (🥈33 · ⭐ 8.6K · 💤) - 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) (👨‍💻 340 · 🔀 1.9K · 📦 2 · 📋 1.3K - 10% open · ⏱️ 01.08.2024): ``` git clone https://github.com/VowpalWabbit/vowpal_wabbit ``` - [PyPi](https://pypi.org/project/vowpalwabbit) (📥 49K / month · 📦 40 · ⏱️ 08.08.2024): ``` pip install vowpalwabbit ``` - [Conda](https://anaconda.org/conda-forge/vowpalwabbit) (📥 350K · ⏱️ 22.04.2025): ``` conda install -c conda-forge vowpalwabbit ``` </details> <details><summary><b><a href="https://github.com/mlpack/mlpack">mlpack</a></b> (🥈33 · ⭐ 5.3K) - 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) (👨‍💻 330 · 🔀 1.7K · 📋 1.6K - 0% open · ⏱️ 22.04.2025): ``` git clone https://github.com/mlpack/mlpack ``` - [PyPi](https://pypi.org/project/mlpack) (📥 7.2K / month · 📦 6 · ⏱️ 04.04.2025): ``` pip install mlpack ``` - [Conda](https://anaconda.org/conda-forge/mlpack) (📥 350K · ⏱️ 22.04.2025): ``` conda install -c conda-forge mlpack ``` </details> <details><summary><b><a href="https://github.com/ludwig-ai/ludwig">Ludwig</a></b> (🥉32 · ⭐ 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) (👨‍💻 160 · 🔀 1.2K · 📦 300 · 📋 1.1K - 4% open · ⏱️ 17.10.2024): ``` git clone https://github.com/ludwig-ai/ludwig ``` - [PyPi](https://pypi.org/project/ludwig) (📥 2.5K / month · 📦 6 · ⏱️ 30.07.2024): ``` pip install ludwig ``` </details> <details><summary><b><a href="https://github.com/google-deepmind/sonnet">Sonnet</a></b> (🥉32 · ⭐ 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) (👨‍💻 61 · 🔀 1.3K · 📦 1.4K · 📋 190 - 16% open · ⏱️ 14.02.2025): ``` git clone https://github.com/deepmind/sonnet ``` - [PyPi](https://pypi.org/project/dm-sonnet) (📥 22K / month · 📦 19 · ⏱️ 02.01.2024): ``` pip install dm-sonnet ``` - [Conda](https://anaconda.org/conda-forge/sonnet) (📥 41K · ⏱️ 22.04.2025): ``` conda install -c conda-forge sonnet ``` </details> <details><summary><b><a href="https://github.com/skorch-dev/skorch">skorch</a></b> (🥉32 · ⭐ 6K) - 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) (👨‍💻 67 · 🔀 390 · 📦 1.6K · 📋 540 - 12% open · ⏱️ 24.04.2025): ``` git clone https://github.com/skorch-dev/skorch ``` - [PyPi](https://pypi.org/project/skorch) (📥 130K / month · 📦 94 · ⏱️ 10.01.2025): ``` pip install skorch ``` - [Conda](https://anaconda.org/conda-forge/skorch) (📥 800K · ⏱️ 22.04.2025): ``` conda install -c conda-forge skorch ``` </details> <details><summary><b><a href="https://github.com/google-deepmind/dm-haiku">Haiku</a></b> (🥉31 · ⭐ 3K) - 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) (👨‍💻 85 · 🔀 240 · 📦 2.4K · 📋 250 - 29% open · ⏱️ 22.04.2025): ``` git clone https://github.com/deepmind/dm-haiku ``` - [PyPi](https://pypi.org/project/dm-haiku) (📥 190K / month · 📦 190 · ⏱️ 22.04.2025): ``` pip install dm-haiku ``` - [Conda](https://anaconda.org/conda-forge/dm-haiku) (📥 32K · ⏱️ 23.04.2025): ``` conda install -c conda-forge dm-haiku ``` </details> <details><summary><b><a href="https://github.com/ROCm/tensorflow-upstream">tensorflow-upstream</a></b> (🥉31 · ⭐ 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) (👨‍💻 4.9K · 🔀 99 · 📥 29 · 📋 390 - 4% open · ⏱️ 21.04.2025): ``` git clone https://github.com/ROCmSoftwarePlatform/tensorflow-upstream ``` - [PyPi](https://pypi.org/project/tensorflow-rocm) (📥 6.1K / month · 📦 9 · ⏱️ 10.01.2024): ``` pip install tensorflow-rocm ``` </details> <details><summary><b><a href="https://github.com/determined-ai/determined">Determined</a></b> (🥉30 · ⭐ 3.1K) - 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[PyPi](https://pypi.org/project/geomstats) (📥 5.5K / month · 📦 12 · ⏱️ 09.09.2024): ``` pip install geomstats ``` - [Conda](https://anaconda.org/conda-forge/geomstats) (📥 6.2K · ⏱️ 22.04.2025): ``` conda install -c conda-forge geomstats ``` </details> <details><summary><b><a href="https://github.com/numenta/nupic-legacy">NuPIC</a></b> (🥉28 · ⭐ 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) (👨‍💻 120 · 🔀 1.6K · 📥 21 · 📦 21 · 📋 1.8K - 25% open · ⏱️ 03.12.2024): ``` git clone https://github.com/numenta/nupic ``` - [PyPi](https://pypi.org/project/nupic) (📥 2.4K / month · ⏱️ 01.09.2016): ``` pip install nupic ``` </details> <details><summary><b><a href="https://github.com/amaiya/ktrain">ktrain</a></b> (🥉27 · ⭐ 1.3K · 💤) - ktrain is a Python library that makes deep learning and AI.. <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) (👨‍💻 17 · 🔀 270 · 📦 570 · 📋 500 - 0% open · ⏱️ 09.07.2024): ``` git clone https://github.com/amaiya/ktrain ``` - [PyPi](https://pypi.org/project/ktrain) (📥 8K / month · 📦 4 · ⏱️ 19.06.2024): ``` pip install ktrain ``` </details> <details><summary><b><a href="https://github.com/pyRiemann/pyRiemann">pyRiemann</a></b> (🥉27 · ⭐ 680) - 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) (👨‍💻 37 · 🔀 170 · 📦 450 · 📋 110 - 2% open · ⏱️ 17.04.2025): ``` git clone https://github.com/pyRiemann/pyRiemann ``` - [PyPi](https://pypi.org/project/pyriemann) (📥 53K / month · 📦 28 · ⏱️ 12.02.2025): ``` pip install pyriemann ``` - [Conda](https://anaconda.org/conda-forge/pyriemann) (📥 12K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pyriemann ``` </details> <details><summary><b><a href="https://github.com/sony/nnabla">Neural Network Libraries</a></b> (🥉26 · ⭐ 2.7K) - 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[GitHub](https://github.com/nubank/fklearn) (👨‍💻 56 · 🔀 170 · 📦 16 · 📋 64 - 60% open · ⏱️ 23.04.2025): ``` git clone https://github.com/nubank/fklearn ``` - [PyPi](https://pypi.org/project/fklearn) (📥 2.4K / month · ⏱️ 26.02.2025): ``` pip install fklearn ``` </details> <details><summary><b><a href="https://github.com/run-house/runhouse">Runhouse</a></b> (🥉23 · ⭐ 1K) - Distribute and run AI workloads magically in Python, like PyTorch for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/run-house/runhouse) (👨‍💻 16 · 🔀 36 · 📥 69 · 📋 51 - 17% open · ⏱️ 03.04.2025): ``` git clone https://github.com/run-house/runhouse ``` - [PyPi](https://pypi.org/project/runhouse) (📥 25K / month · 📦 1 · ⏱️ 10.03.2025): ``` pip install runhouse ``` </details> <details><summary><b><a href="https://github.com/Xtra-Computing/thundersvm">ThunderSVM</a></b> (🥉22 · ⭐ 1.6K · 💤) - 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) (👨‍💻 37 · 🔀 220 · 📥 3K · 📋 230 - 35% open · ⏱️ 01.04.2024): ``` git clone https://github.com/Xtra-Computing/thundersvm ``` - [PyPi](https://pypi.org/project/thundersvm) (📥 1.6K / month · ⏱️ 13.03.2020): ``` pip install thundersvm ``` </details> <details><summary><b><a href="https://github.com/neoml-lib/neoml">NeoML</a></b> (🥉20 · ⭐ 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) (👨‍💻 40 · 🔀 130 · 📦 2 · 📋 91 - 40% open · ⏱️ 30.09.2024): ``` git clone https://github.com/neoml-lib/neoml ``` - [PyPi](https://pypi.org/project/neoml) (📥 1.5K / month · ⏱️ 26.12.2023): ``` pip install neoml ``` </details> <details><summary><b><a href="https://github.com/serengil/chefboost">chefboost</a></b> (🥉20 · ⭐ 480) - 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) (👨‍💻 7 · 🔀 100 · 📦 69 · ⏱️ 31.03.2025): ``` git clone https://github.com/serengil/chefboost ``` - [PyPi](https://pypi.org/project/chefboost) (📥 7.4K / month · ⏱️ 30.10.2024): ``` pip install chefboost ``` </details> <details><summary><b><a href="https://github.com/Xtra-Computing/thundergbm">ThunderGBM</a></b> (🥉18 · ⭐ 700) - 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) (👨‍💻 12 · 🔀 87 · 📦 4 · 📋 81 - 48% open · ⏱️ 19.03.2025): ``` git clone https://github.com/Xtra-Computing/thundergbm ``` - [PyPi](https://pypi.org/project/thundergbm) (📥 540 / month · ⏱️ 19.09.2022): ``` pip install thundergbm ``` </details> <details><summary>Show 23 hidden projects...</summary> - <b><a href="https://github.com/davisking/dlib">dlib</a></b> (🥈40 · ⭐ 14K) - A toolkit for making real world machine learning and data analysis.. <code><a href="https://tldrlegal.com/search?q=BSL-1.0">❗️BSL-1.0</a></code> - <b><a href="https://github.com/apache/mxnet">MXNet</a></b> (🥈39 · ⭐ 21K · 💀) - 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/Theano/Theano">Theano</a></b> (🥈38 · ⭐ 9.9K · 💀) - Theano was a Python library that allows you to define, optimize, and.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> - <b><a href="https://github.com/chainer/chainer">Chainer</a></b> (🥈34 · ⭐ 5.9K · 💀) - 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> (🥈33 · ⭐ 28K) - AIs query engine - Platform for building AI that can learn and.. <code><a href="https://tldrlegal.com/search?q=ICU">❗️ICU</a></code> <code><img src="https://git.io/JLy1Q" style="display:inline;" width="13" height="13"></code> - <b><a href="https://github.com/tensorpack/tensorpack">tensorpack</a></b> (🥈33 · ⭐ 6.3K · 💀) - 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/apple/turicreate">Turi Create</a></b> (🥉32 · ⭐ 11K · 💀) - 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/tflearn/tflearn">TFlearn</a></b> (🥉31 · ⭐ 9.6K · 💀) - 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> (🥉31 · ⭐ 3.4K · 💀) - 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> (🥉29 · ⭐ 18K · 💀) - 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> (🥉28 · ⭐ 3.9K · 💀) - 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/shogun-toolbox/shogun">SHOGUN</a></b> (🥉27 · ⭐ 3K · 💀) - Unified and efficient Machine Learning. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> - <b><a href="https://github.com/georgia-tech-db/evadb">EvaDB</a></b> (🥉27 · ⭐ 2.7K · 💀) - 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> - <b><a href="https://github.com/aksnzhy/xlearn">xLearn</a></b> (🥉25 · ⭐ 3.1K · 💀) - 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> (🥉24 · ⭐ 3.9K · 💀) - 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/google/neural-tangents">Neural Tangents</a></b> (🥉24 · ⭐ 2.3K · 💀) - Fast and Easy Infinite Neural Networks in Python. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/itdxer/neupy">NeuPy</a></b> (🥉24 · ⭐ 740 · 💀) - 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/pytorchbearer/torchbearer">Torchbearer</a></b> (🥉22 · ⭐ 640 · 💀) - 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> - <b><a href="https://github.com/XiaoMi/mace">mace</a></b> (🥉21 · ⭐ 5K · 💀) - MACE is a deep learning inference framework optimized for mobile.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/poets-ai/elegy">elegy</a></b> (🥉20 · ⭐ 480 · 💀) - 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/google/objax">Objax</a></b> (🥉19 · ⭐ 770 · 💀) - 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> - <b><a href="https://github.com/facebookresearch/StarSpace">StarSpace</a></b> (🥉16 · ⭐ 4K · 💀) - 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> (🥉14 · ⭐ 290 · 💤) - A Jax-based library for designing and training small transformers. <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> (🥇49 · ⭐ 21K) - matplotlib: plotting with Python. <code>❗Unlicensed</code></summary> - [GitHub](https://github.com/matplotlib/matplotlib) (👨‍💻 1.8K · 🔀 7.8K · 📦 1.7M · 📋 11K - 14% open · ⏱️ 24.04.2025): ``` git clone https://github.com/matplotlib/matplotlib ``` - [PyPi](https://pypi.org/project/matplotlib) (📥 85M / month · 📦 56K · ⏱️ 27.02.2025): ``` pip install matplotlib ``` - [Conda](https://anaconda.org/conda-forge/matplotlib) (📥 30M · ⏱️ 22.04.2025): ``` conda install -c conda-forge matplotlib ``` </details> <details><summary><b><a href="https://github.com/plotly/dash">dash</a></b> (🥇46 · ⭐ 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) (👨‍💻 180 · 🔀 2.1K · 📥 88 · 📦 84K · 📋 2K - 27% open · ⏱️ 24.04.2025): ``` git clone https://github.com/plotly/dash ``` - [PyPi](https://pypi.org/project/dash) (📥 5.5M / month · 📦 1.6K · ⏱️ 14.04.2025): ``` pip install dash ``` - [Conda](https://anaconda.org/conda-forge/dash) (📥 1.8M · ⏱️ 22.04.2025): ``` conda install -c conda-forge dash ``` </details> <details><summary><b><a href="https://github.com/plotly/plotly.py">Plotly</a></b> (🥇46 · ⭐ 17K) - The interactive graphing library for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/plotly/plotly.py) (👨‍💻 280 · 🔀 2.6K · 📥 160 · 📦 410K · 📋 3.2K - 20% open · ⏱️ 22.04.2025): ``` git clone https://github.com/plotly/plotly.py ``` - [PyPi](https://pypi.org/project/plotly) (📥 23M / month · 📦 7.8K · ⏱️ 31.03.2025): ``` pip install plotly ``` - [Conda](https://anaconda.org/conda-forge/plotly) (📥 9.2M · ⏱️ 22.04.2025): ``` conda install -c conda-forge plotly ``` - [npm](https://www.npmjs.com/package/plotlywidget) (📥 57K / month · 📦 9 · ⏱️ 12.01.2021): ``` npm install plotlywidget ``` </details> <details><summary><b><a href="https://github.com/bokeh/bokeh">Bokeh</a></b> (🥇45 · ⭐ 20K) - 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) (👨‍💻 710 · 🔀 4.2K · 📦 100K · 📋 7.9K - 10% open · ⏱️ 24.04.2025): ``` git clone https://github.com/bokeh/bokeh ``` - [PyPi](https://pypi.org/project/bokeh) (📥 3.7M / month · 📦 1.9K · ⏱️ 28.03.2025): ``` pip install bokeh ``` - [Conda](https://anaconda.org/conda-forge/bokeh) (📥 16M · ⏱️ 22.04.2025): ``` conda install -c conda-forge bokeh ``` </details> <details><summary><b><a href="https://github.com/mwaskom/seaborn">Seaborn</a></b> (🥇43 · ⭐ 13K) - Statistical data visualization in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/mwaskom/seaborn) (👨‍💻 220 · 🔀 1.9K · 📥 470 · 📦 630K · 📋 2.6K - 6% open · ⏱️ 26.01.2025): ``` git clone https://github.com/mwaskom/seaborn ``` - [PyPi](https://pypi.org/project/seaborn) (📥 25M / month · 📦 11K · ⏱️ 25.01.2024): ``` pip install seaborn ``` - [Conda](https://anaconda.org/conda-forge/seaborn) (📥 12M · ⏱️ 22.04.2025): ``` conda install -c conda-forge seaborn ``` </details> <details><summary><b><a href="https://github.com/vega/altair">Altair</a></b> (🥇42 · ⭐ 9.7K) - Declarative visualization library for Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/vega/altair) (👨‍💻 180 · 🔀 800 · 📥 230 · 📦 220K · 📋 2.1K - 6% open · ⏱️ 22.04.2025): ``` git clone https://github.com/altair-viz/altair ``` - [PyPi](https://pypi.org/project/altair) (📥 28M / month · 📦 920 · ⏱️ 23.11.2024): ``` pip install altair ``` - [Conda](https://anaconda.org/conda-forge/altair) (📥 2.7M · ⏱️ 22.04.2025): ``` conda install -c conda-forge altair ``` </details> <details><summary><b><a href="https://github.com/voxel51/fiftyone">FiftyOne</a></b> (🥈39 · ⭐ 9.4K) - 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) (👨‍💻 150 · 🔀 620 · 📦 930 · 📋 1.7K - 33% open · ⏱️ 24.04.2025): ``` git clone https://github.com/voxel51/fiftyone ``` - [PyPi](https://pypi.org/project/fiftyone) (📥 150K / month · 📦 26 · ⏱️ 04.04.2025): ``` pip install fiftyone ``` </details> <details><summary><b><a href="https://github.com/pyvista/pyvista">PyVista</a></b> (🥈39 · ⭐ 3K) - 3D plotting and mesh analysis through a streamlined interface for the.. <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) (👨‍💻 170 · 🔀 550 · 📥 890 · 📦 4.6K · 📋 1.9K - 36% open · ⏱️ 24.04.2025): ``` git clone https://github.com/pyvista/pyvista ``` - [PyPi](https://pypi.org/project/pyvista) (📥 600K / month · 📦 690 · ⏱️ 19.04.2025): ``` pip install pyvista ``` - [Conda](https://anaconda.org/conda-forge/pyvista) (📥 670K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pyvista ``` </details> <details><summary><b><a href="https://github.com/ydataai/ydata-profiling">pandas-profiling</a></b> (🥈38 · ⭐ 13K) - 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) (👨‍💻 140 · 🔀 1.7K · 📥 310 · 📦 6.2K · 📋 840 - 29% open · ⏱️ 26.03.2025): ``` git clone https://github.com/ydataai/pandas-profiling ``` - [PyPi](https://pypi.org/project/pandas-profiling) (📥 370K / month · 📦 180 · ⏱️ 03.02.2023): ``` pip install pandas-profiling ``` - [Conda](https://anaconda.org/conda-forge/pandas-profiling) (📥 510K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pandas-profiling ``` </details> <details><summary><b><a href="https://github.com/holoviz/holoviews">HoloViews</a></b> (🥈38 · ⭐ 2.8K · 📉) - 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) (👨‍💻 150 · 🔀 410 · 📦 15K · 📋 3.4K - 32% open · ⏱️ 23.04.2025): ``` git clone https://github.com/holoviz/holoviews ``` - [PyPi](https://pypi.org/project/holoviews) (📥 510K / month · 📦 430 · ⏱️ 31.03.2025): ``` pip install holoviews ``` - [Conda](https://anaconda.org/conda-forge/holoviews) (📥 2M · ⏱️ 22.04.2025): ``` conda install -c conda-forge holoviews ``` - [npm](https://www.npmjs.com/package/@pyviz/jupyterlab_pyviz) (📥 220 / month · 📦 5 · ⏱️ 14.01.2025): ``` npm install @pyviz/jupyterlab_pyviz ``` </details> <details><summary><b><a href="https://github.com/pyqtgraph/pyqtgraph">PyQtGraph</a></b> (🥈37 · ⭐ 4.1K) - 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) (👨‍💻 300 · 🔀 1.1K · 📦 12K · 📋 1.3K - 32% open · ⏱️ 08.04.2025): ``` git clone https://github.com/pyqtgraph/pyqtgraph ``` - [PyPi](https://pypi.org/project/pyqtgraph) (📥 390K / month · 📦 1K · ⏱️ 29.04.2024): ``` pip install pyqtgraph ``` - [Conda](https://anaconda.org/conda-forge/pyqtgraph) (📥 680K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pyqtgraph ``` </details> <details><summary><b><a href="https://github.com/pyecharts/pyecharts">pyecharts</a></b> (🥈36 · ⭐ 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) (👨‍💻 45 · 🔀 2.9K · 📥 73 · 📦 5.3K · 📋 1.9K - 0% open · ⏱️ 26.01.2025): ``` git clone https://github.com/pyecharts/pyecharts ``` - [PyPi](https://pypi.org/project/pyecharts) (📥 200K / month · 📦 220 · ⏱️ 24.01.2025): ``` pip install pyecharts ``` </details> <details><summary><b><a href="https://github.com/has2k1/plotnine">plotnine</a></b> (🥈36 · ⭐ 4.2K) - A Grammar of Graphics for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/has2k1/plotnine) (👨‍💻 110 · 🔀 230 · 📦 12K · 📋 710 - 10% open · ⏱️ 22.04.2025): ``` git clone https://github.com/has2k1/plotnine ``` - [PyPi](https://pypi.org/project/plotnine) (📥 2.3M / month · 📦 370 · ⏱️ 23.04.2025): ``` pip install plotnine ``` - [Conda](https://anaconda.org/conda-forge/plotnine) (📥 460K · ⏱️ 22.04.2025): ``` conda install -c conda-forge plotnine ``` </details> <details><summary><b><a href="https://github.com/xflr6/graphviz">Graphviz</a></b> (🥈36 · ⭐ 1.7K · 💤) - Simple Python interface for Graphviz. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/xflr6/graphviz) (👨‍💻 23 · 🔀 210 · 📦 88K · 📋 190 - 6% open · ⏱️ 13.05.2024): ``` git clone https://github.com/xflr6/graphviz ``` - [PyPi](https://pypi.org/project/graphviz) (📥 18M / month · 📦 2.9K · ⏱️ 21.03.2024): ``` pip install graphviz ``` - [Conda](https://anaconda.org/anaconda/python-graphviz) (📥 54K · ⏱️ 22.04.2025): ``` conda install -c anaconda python-graphviz ``` </details> <details><summary><b><a href="https://github.com/vispy/vispy">VisPy</a></b> (🥈35 · ⭐ 3.4K · 📈) - 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) (👨‍💻 200 · 🔀 620 · 📦 2K · 📋 1.5K - 25% open · ⏱️ 22.04.2025): ``` git clone https://github.com/vispy/vispy ``` - [PyPi](https://pypi.org/project/vispy) (📥 150K / month · 📦 200 · ⏱️ 22.04.2025): ``` pip install vispy ``` - [Conda](https://anaconda.org/conda-forge/vispy) (📥 790K · ⏱️ 22.04.2025): ``` conda install -c conda-forge vispy ``` - [npm](https://www.npmjs.com/package/vispy) (📥 23 / month · 📦 3 · ⏱️ 15.03.2020): ``` npm install vispy ``` </details> <details><summary><b><a href="https://github.com/finos/perspective">Perspective</a></b> (🥈34 · ⭐ 9.1K) - 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) (👨‍💻 99 · 🔀 1.2K · 📥 11K · 📦 180 · 📋 880 - 12% open · ⏱️ 11.04.2025): ``` git clone https://github.com/finos/perspective ``` - [PyPi](https://pypi.org/project/perspective-python) (📥 20K / month · 📦 30 · ⏱️ 11.04.2025): ``` pip install perspective-python ``` - [Conda](https://anaconda.org/conda-forge/perspective) (📥 2M · ⏱️ 22.04.2025): ``` conda install -c conda-forge perspective ``` - [npm](https://www.npmjs.com/package/@finos/perspective-jupyterlab) (📥 680 / month · 📦 6 · ⏱️ 11.04.2025): ``` npm install @finos/perspective-jupyterlab ``` </details> <details><summary><b><a href="https://github.com/holoviz/datashader">datashader</a></b> (🥈34 · ⭐ 3.4K) - 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) (👨‍💻 62 · 🔀 370 · 📦 5.9K · 📋 600 - 23% open · ⏱️ 10.04.2025): ``` git clone https://github.com/holoviz/datashader ``` - [PyPi](https://pypi.org/project/datashader) (📥 190K / month · 📦 240 · ⏱️ 10.04.2025): ``` pip install datashader ``` - [Conda](https://anaconda.org/conda-forge/datashader) (📥 1.4M · ⏱️ 22.04.2025): ``` conda install -c conda-forge datashader ``` </details> <details><summary><b><a href="https://github.com/SciTools/cartopy">cartopy</a></b> (🥈34 · ⭐ 1.5K) - 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) (👨‍💻 130 · 🔀 380 · 📦 7.3K · 📋 1.3K - 24% open · ⏱️ 17.04.2025): ``` git clone https://github.com/SciTools/cartopy ``` - [PyPi](https://pypi.org/project/cartopy) (📥 550K / month · 📦 720 · ⏱️ 08.10.2024): ``` pip install cartopy ``` - [Conda](https://anaconda.org/conda-forge/cartopy) (📥 4.7M · ⏱️ 22.04.2025): ``` conda install -c conda-forge cartopy ``` </details> <details><summary><b><a href="https://github.com/amueller/word_cloud">wordcloud</a></b> (🥈33 · ⭐ 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) (👨‍💻 73 · 🔀 2.3K · 📦 21 · 📋 560 - 24% open · ⏱️ 12.04.2025): ``` git clone https://github.com/amueller/word_cloud ``` - [PyPi](https://pypi.org/project/wordcloud) (📥 1.8M / month · 📦 550 · ⏱️ 10.11.2024): ``` pip install wordcloud ``` - [Conda](https://anaconda.org/conda-forge/wordcloud) (📥 660K · ⏱️ 22.04.2025): ``` conda install -c conda-forge wordcloud ``` </details> <details><summary><b><a href="https://github.com/JetBrains/lets-plot">lets-plot</a></b> (🥈33 · ⭐ 1.7K) - 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) (👨‍💻 21 · 🔀 53 · 📥 3.2K · 📦 180 · 📋 680 - 23% open · ⏱️ 21.04.2025): ``` git clone https://github.com/JetBrains/lets-plot ``` - [PyPi](https://pypi.org/project/lets-plot) (📥 54K / month · 📦 15 · ⏱️ 28.03.2025): ``` pip install lets-plot ``` </details> <details><summary><b><a href="https://github.com/lmcinnes/umap">UMAP</a></b> (🥈32 · ⭐ 7.7K) - Uniform Manifold Approximation and Projection. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/lmcinnes/umap) (👨‍💻 140 · 🔀 820 · 📦 1 · 📋 850 - 59% open · ⏱️ 28.02.2025): ``` git clone https://github.com/lmcinnes/umap ``` - [PyPi](https://pypi.org/project/umap-learn) (📥 1.6M / month · 📦 1.1K · ⏱️ 28.10.2024): ``` pip install umap-learn ``` - [Conda](https://anaconda.org/conda-forge/umap-learn) (📥 3M · ⏱️ 22.04.2025): ``` conda install -c conda-forge umap-learn ``` </details> <details><summary><b><a href="https://github.com/holoviz/hvplot">hvPlot</a></b> (🥈32 · ⭐ 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) (👨‍💻 51 · 🔀 110 · 📦 7K · 📋 860 - 43% open · ⏱️ 16.04.2025): ``` git clone https://github.com/holoviz/hvplot ``` - [PyPi](https://pypi.org/project/hvplot) (📥 210K / month · 📦 220 · ⏱️ 16.12.2024): ``` pip install hvplot ``` - [Conda](https://anaconda.org/conda-forge/hvplot) (📥 750K · ⏱️ 22.04.2025): ``` conda install -c conda-forge hvplot ``` </details> <details><summary><b><a href="https://github.com/mpld3/mpld3">mpld3</a></b> (🥉31 · ⭐ 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) (👨‍💻 53 · 🔀 360 · 📦 7.3K · 📋 370 - 59% open · ⏱️ 30.10.2024): ``` git clone https://github.com/mpld3/mpld3 ``` - [PyPi](https://pypi.org/project/mpld3) (📥 340K / month · 📦 150 · ⏱️ 23.12.2023): ``` pip install mpld3 ``` - [Conda](https://anaconda.org/conda-forge/mpld3) (📥 230K · ⏱️ 22.04.2025): ``` conda install -c conda-forge mpld3 ``` - [npm](https://www.npmjs.com/package/mpld3) (📥 1.1K / month · 📦 9 · ⏱️ 23.12.2023): ``` npm install mpld3 ``` </details> <details><summary><b><a href="https://github.com/man-group/dtale">D-Tale</a></b> (🥉30 · ⭐ 4.9K) - Visualizer for pandas data structures. <code><a href="https://tldrlegal.com/search?q=LGPL-2.1">❗️LGPL-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) (👨‍💻 30 · 🔀 420 · 📦 1.4K · 📋 600 - 10% open · ⏱️ 20.03.2025): ``` git clone https://github.com/man-group/dtale ``` - [PyPi](https://pypi.org/project/dtale) (📥 180K / month · 📦 53 · ⏱️ 20.03.2025): ``` pip install dtale ``` - [Conda](https://anaconda.org/conda-forge/dtale) (📥 410K · ⏱️ 22.04.2025): ``` conda install -c conda-forge dtale ``` </details> <details><summary><b><a href="https://github.com/bqplot/bqplot">bqplot</a></b> (🥉30 · ⭐ 3.7K) - 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) (👨‍💻 65 · 🔀 470 · 📦 61 · 📋 640 - 42% open · ⏱️ 22.10.2024): ``` git clone https://github.com/bqplot/bqplot ``` - [PyPi](https://pypi.org/project/bqplot) (📥 180K / month · 📦 110 · ⏱️ 24.12.2024): ``` pip install bqplot ``` - [Conda](https://anaconda.org/conda-forge/bqplot) (📥 1.6M · ⏱️ 22.04.2025): ``` conda install -c conda-forge bqplot ``` - [npm](https://www.npmjs.com/package/bqplot) (📥 2K / month · 📦 21 · ⏱️ 24.12.2024): ``` npm install bqplot ``` </details> <details><summary><b><a href="https://github.com/AutoViML/AutoViz">AutoViz</a></b> (🥉27 · ⭐ 1.8K · 💤) - Automatically Visualize any dataset, any size with a single line.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/AutoViML/AutoViz) (👨‍💻 17 · 🔀 200 · 📦 860 · 📋 98 - 2% open · ⏱️ 10.06.2024): ``` git clone https://github.com/AutoViML/AutoViz ``` - [PyPi](https://pypi.org/project/autoviz) (📥 17K / month · 📦 11 · ⏱️ 10.06.2024): ``` pip install autoviz ``` - [Conda](https://anaconda.org/conda-forge/autoviz) (📥 83K · ⏱️ 22.04.2025): ``` conda install -c conda-forge autoviz ``` </details> <details><summary><b><a href="https://github.com/pavlin-policar/openTSNE">openTSNE</a></b> (🥉27 · ⭐ 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) (👨‍💻 13 · 🔀 170 · 📦 1K · 📋 140 - 7% open · ⏱️ 24.10.2024): ``` git clone https://github.com/pavlin-policar/openTSNE ``` - [PyPi](https://pypi.org/project/opentsne) (📥 43K / month · 📦 47 · ⏱️ 13.08.2024): ``` pip install opentsne ``` - [Conda](https://anaconda.org/conda-forge/opentsne) (📥 420K · ⏱️ 22.04.2025): ``` conda install -c conda-forge opentsne ``` </details> <details><summary><b><a href="https://github.com/predict-idlab/plotly-resampler">Plotly-Resampler</a></b> (🥉27 · ⭐ 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) (👨‍💻 14 · 🔀 72 · 📦 1.9K · 📋 180 - 32% open · ⏱️ 07.04.2025): ``` git clone https://github.com/predict-idlab/plotly-resampler ``` - [PyPi](https://pypi.org/project/plotly-resampler) (📥 480K / month · 📦 31 · ⏱️ 07.04.2025): ``` pip install plotly-resampler ``` - [Conda](https://anaconda.org/conda-forge/plotly-resampler) (📥 110K · ⏱️ 22.04.2025): ``` conda install -c conda-forge plotly-resampler ``` </details> <details><summary><b><a href="https://github.com/spotify/chartify">Chartify</a></b> (🥉25 · ⭐ 3.6K) - 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) (👨‍💻 27 · 🔀 320 · 📦 82 · 📋 83 - 61% open · ⏱️ 16.10.2024): ``` git clone https://github.com/spotify/chartify ``` - [PyPi](https://pypi.org/project/chartify) (📥 2K / month · 📦 9 · ⏱️ 16.10.2024): ``` pip install chartify ``` - [Conda](https://anaconda.org/conda-forge/chartify) (📥 37K · ⏱️ 22.04.2025): ``` conda install -c conda-forge chartify ``` </details> <details><summary><b><a href="https://github.com/tensorflow/data-validation">data-validation</a></b> (🥉25 · ⭐ 770) - 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) (👨‍💻 27 · 🔀 170 · 📥 980 · 📋 180 - 21% open · ⏱️ 12.03.2025): ``` git clone https://github.com/tensorflow/data-validation ``` - [PyPi](https://pypi.org/project/tensorflow-data-validation) (📥 140K / month · 📦 31 · ⏱️ 15.10.2024): ``` pip install tensorflow-data-validation ``` </details> <details><summary><b><a href="https://github.com/marcharper/python-ternary">python-ternary</a></b> (🥉25 · ⭐ 760 · 💤) - 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) (👨‍💻 28 · 🔀 160 · 📥 36 · 📦 220 · 📋 140 - 24% open · ⏱️ 12.06.2024): ``` git clone https://github.com/marcharper/python-ternary ``` - [PyPi](https://pypi.org/project/python-ternary) (📥 19K / month · 📦 32 · ⏱️ 17.02.2021): ``` pip install python-ternary ``` - [Conda](https://anaconda.org/conda-forge/python-ternary) (📥 100K · ⏱️ 22.04.2025): ``` conda install -c conda-forge python-ternary ``` </details> <details><summary><b><a href="https://github.com/gyli/PyWaffle">PyWaffle</a></b> (🥉22 · ⭐ 600 · 💤) - Make Waffle Charts in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/gyli/PyWaffle) (👨‍💻 6 · 🔀 110 · 📦 510 · 📋 22 - 27% open · ⏱️ 16.06.2024): ``` git clone https://github.com/gyli/PyWaffle ``` - [PyPi](https://pypi.org/project/pywaffle) (📥 13K / month · 📦 6 · ⏱️ 16.06.2024): ``` pip install pywaffle ``` - [Conda](https://anaconda.org/conda-forge/pywaffle) (📥 16K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pywaffle ``` </details> <details><summary><b><a href="https://github.com/vega/ipyvega">vega</a></b> (🥉22 · ⭐ 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) (👨‍💻 15 · 🔀 65 · 📦 4 · 📋 110 - 14% open · ⏱️ 01.01.2025): ``` git clone https://github.com/vega/ipyvega ``` - [PyPi](https://pypi.org/project/vega) (📥 17K / month · 📦 17 · ⏱️ 25.09.2024): ``` pip install vega ``` - [Conda](https://anaconda.org/conda-forge/vega) (📥 730K · ⏱️ 22.04.2025): ``` conda install -c conda-forge vega ``` </details> <details><summary><b><a href="https://github.com/ing-bank/popmon">Popmon</a></b> (🥉21 · ⭐ 500) - 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></summary> - [GitHub](https://github.com/ing-bank/popmon) (👨‍💻 19 · 🔀 36 · 📥 260 · 📦 22 · 📋 57 - 28% open · ⏱️ 24.01.2025): ``` git clone https://github.com/ing-bank/popmon ``` - [PyPi](https://pypi.org/project/popmon) (📥 13K / month · 📦 4 · ⏱️ 24.01.2025): ``` pip install popmon ``` </details> <details><summary><b><a href="https://github.com/t-makaro/animatplot">animatplot</a></b> (🥉20 · ⭐ 420 · 💤) - 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) (👨‍💻 6 · 🔀 38 · 📦 74 · 📋 37 - 45% open · ⏱️ 29.08.2024): ``` git clone https://github.com/t-makaro/animatplot ``` - [PyPi](https://pypi.org/project/animatplot) (📥 850 / month · 📦 4 · ⏱️ 29.08.2024): ``` pip install animatplot ``` - [Conda](https://anaconda.org/conda-forge/animatplot) (📥 17K · ⏱️ 22.04.2025): ``` conda install -c conda-forge animatplot ``` </details> <details><summary><b><a href="https://github.com/vega/vegafusion">vegafusion</a></b> (🥉20 · ⭐ 350) - 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) (👨‍💻 6 · 🔀 20 · 📥 12K · 📋 140 - 36% open · ⏱️ 23.02.2025): ``` git clone https://github.com/vegafusion/vegafusion ``` - [PyPi](https://pypi.org/project/vegafusion-jupyter) (📥 2.4K / month · 📦 2 · ⏱️ 09.05.2024): ``` pip install vegafusion-jupyter ``` - [Conda](https://anaconda.org/conda-forge/vegafusion-python-embed) (📥 420K · ⏱️ 22.04.2025): ``` conda install -c conda-forge vegafusion-python-embed ``` - [npm](https://www.npmjs.com/package/vegafusion-jupyter) (📥 310 / month · 📦 3 · ⏱️ 09.05.2024): ``` npm install vegafusion-jupyter ``` </details> <details><summary><b><a href="https://github.com/beringresearch/ivis">ivis</a></b> (🥉19 · ⭐ 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) (👨‍💻 10 · 🔀 43 · 📦 37 · 📋 60 - 5% open · ⏱️ 29.09.2024): ``` git clone https://github.com/beringresearch/ivis ``` - [PyPi](https://pypi.org/project/ivis) (📥 1.8K / month · 📦 2 · ⏱️ 13.06.2024): ``` pip install ivis ``` </details> <details><summary>Show 18 hidden projects...</summary> - <b><a href="https://github.com/ResidentMario/missingno">missingno</a></b> (🥉30 · ⭐ 4.1K · 💀) - 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> (🥉28 · ⭐ 3.1K · 💀) - 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> (🥉28 · ⭐ 960 · 💀) - 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> (🥉27 · ⭐ 7.4K · 💀) - 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> (🥉27 · ⭐ 3K · 💀) - 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/facebookresearch/hiplot">HiPlot</a></b> (🥉26 · ⭐ 2.8K · 💀) - HiPlot makes understanding high dimensional data easy. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/ContextLab/hypertools">HyperTools</a></b> (🥉25 · ⭐ 1.8K · 💀) - A Python toolbox for gaining geometric insights into high-.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/adamerose/PandasGUI">PandasGUI</a></b> (🥉24 · ⭐ 3.2K · 💀) - A GUI for Pandas DataFrames. <code><a href="https://tldrlegal.com/search?q=MIT-0">❗️MIT-0</a></code> <code><img src="https://git.io/JLy1S" style="display:inline;" width="13" height="13"></code> - <b><a href="https://github.com/DmitryUlyanov/Multicore-TSNE">Multicore-TSNE</a></b> (🥉24 · ⭐ 1.9K · 💀) - 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> - <b><a href="https://github.com/tpvasconcelos/ridgeplot">ridgeplot</a></b> (🥉24 · ⭐ 230) - Beautiful ridgeline plots in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/PatrikHlobil/Pandas-Bokeh">Pandas-Bokeh</a></b> (🥉22 · ⭐ 880 · 💀) - 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> (🥉22 · ⭐ 700 · 💀) - 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> (🥉22 · ⭐ 590 · 💀) - 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> (🥉21 · ⭐ 850 · 💀) - python partial dependence plot toolbox. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/altair-viz/pdvega">pdvega</a></b> (🥉16 · ⭐ 340 · 💀) - 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> (🥉15 · ⭐ 300 · 💀) - 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> (🥉15 · ⭐ 220 · 💀) - 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> (🥉13 · ⭐ 33 · 💀) - 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> (🥇54 · ⭐ 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) (👨‍💻 3.2K · 🔀 29K · 📦 340K · 📋 18K - 9% open · ⏱️ 24.04.2025): ``` git clone https://github.com/huggingface/transformers ``` - [PyPi](https://pypi.org/project/transformers) (📥 62M / month · 📦 8.4K · ⏱️ 14.04.2025): ``` pip install transformers ``` - [Conda](https://anaconda.org/conda-forge/transformers) (📥 2.7M · ⏱️ 22.04.2025): ``` conda install -c conda-forge transformers ``` </details> <details><summary><b><a href="https://github.com/nltk/nltk">nltk</a></b> (🥇45 · ⭐ 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) (👨‍💻 470 · 🔀 2.9K · 📦 380K · 📋 1.9K - 14% open · ⏱️ 15.03.2025): ``` git clone https://github.com/nltk/nltk ``` - [PyPi](https://pypi.org/project/nltk) (📥 33M / month · 📦 4.7K · ⏱️ 18.08.2024): ``` pip install nltk ``` - [Conda](https://anaconda.org/conda-forge/nltk) (📥 3.1M · ⏱️ 22.04.2025): ``` conda install -c conda-forge nltk ``` </details> <details><summary><b><a href="https://github.com/explosion/spaCy">spaCy</a></b> (🥇43 · ⭐ 31K) - 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) (👨‍💻 760 · 🔀 4.5K · 📥 2.2K · 📦 130K · 📋 5.7K - 3% open · ⏱️ 11.04.2025): ``` git clone https://github.com/explosion/spaCy ``` - [PyPi](https://pypi.org/project/spacy) (📥 18M / month · 📦 3.1K · ⏱️ 01.04.2025): ``` pip install spacy ``` - [Conda](https://anaconda.org/conda-forge/spacy) (📥 5.8M · ⏱️ 22.04.2025): ``` conda install -c conda-forge spacy ``` </details> <details><summary><b><a href="https://github.com/BerriAI/litellm">litellm</a></b> (🥇43 · ⭐ 21K · 📉) - 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) (👨‍💻 490 · 🔀 2.7K · 📥 630 · 📦 11K · 📋 5.5K - 30% open · ⏱️ 24.04.2025): ``` git clone https://github.com/BerriAI/litellm ``` - [PyPi](https://pypi.org/project/litellm) (📥 7.4M / month · 📦 1.1K · ⏱️ 24.04.2025): ``` pip install litellm ``` </details> <details><summary><b><a href="https://github.com/UKPLab/sentence-transformers">sentence-transformers</a></b> (🥇43 · ⭐ 17K · 📉) - 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) (👨‍💻 220 · 🔀 2.6K · 📦 96K · 📋 2.4K - 52% open · ⏱️ 24.04.2025): ``` git clone https://github.com/UKPLab/sentence-transformers ``` - [PyPi](https://pypi.org/project/sentence-transformers) (📥 8.9M / month · 📦 2.4K · ⏱️ 15.04.2025): ``` pip install sentence-transformers ``` - [Conda](https://anaconda.org/conda-forge/sentence-transformers) (📥 660K · ⏱️ 22.04.2025): ``` conda install -c conda-forge sentence-transformers ``` </details> <details><summary><b><a href="https://github.com/flairNLP/flair">flair</a></b> (🥇40 · ⭐ 14K) - A very simple framework for state-of-the-art Natural 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></summary> - [GitHub](https://github.com/flairNLP/flair) (👨‍💻 280 · 🔀 2.1K · 📦 3.9K · 📋 2.4K - 4% open · ⏱️ 31.03.2025): ``` git clone https://github.com/flairNLP/flair ``` - [PyPi](https://pypi.org/project/flair) (📥 110K / month · 📦 150 · ⏱️ 05.02.2025): ``` pip install flair ``` - [Conda](https://anaconda.org/conda-forge/python-flair) (📥 41K · ⏱️ 22.04.2025): ``` conda install -c conda-forge python-flair ``` </details> <details><summary><b><a href="https://github.com/RasaHQ/rasa">Rasa</a></b> (🥇39 · ⭐ 20K) - 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) (👨‍💻 590 · 🔀 4.8K · 📦 5.1K · 📋 6.8K - 2% open · ⏱️ 14.01.2025): ``` git clone https://github.com/RasaHQ/rasa ``` - [PyPi](https://pypi.org/project/rasa) (📥 220K / month · 📦 60 · ⏱️ 14.01.2025): ``` pip install rasa ``` </details> <details><summary><b><a href="https://github.com/huggingface/tokenizers">Tokenizers</a></b> (🥇39 · ⭐ 9.6K) - 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) (👨‍💻 110 · 🔀 870 · 📥 74 · 📦 160K · 📋 1.1K - 7% open · ⏱️ 18.03.2025): ``` git clone https://github.com/huggingface/tokenizers ``` - [PyPi](https://pypi.org/project/tokenizers) (📥 51M / month · 📦 1.3K · ⏱️ 13.03.2025): ``` pip install tokenizers ``` - [Conda](https://anaconda.org/conda-forge/tokenizers) (📥 2.9M · ⏱️ 22.04.2025): ``` conda install -c conda-forge tokenizers ``` </details> <details><summary><b><a href="https://github.com/deepset-ai/haystack">haystack</a></b> (🥇38 · ⭐ 20K) - 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) (👨‍💻 290 · 🔀 2.1K · 📦 1.1K · 📋 3.9K - 3% open · ⏱️ 24.04.2025): ``` git clone https://github.com/deepset-ai/haystack ``` - [PyPi](https://pypi.org/project/haystack) (📥 5.9K / month · 📦 5 · ⏱️ 15.12.2021): ``` pip install haystack ``` </details> <details><summary><b><a href="https://github.com/piskvorky/gensim">gensim</a></b> (🥇38 · ⭐ 16K) - Topic Modelling for Humans. <code><a href="https://tldrlegal.com/search?q=LGPL-2.1">❗️LGPL-2.1</a></code></summary> - [GitHub](https://github.com/piskvorky/gensim) (👨‍💻 460 · 🔀 4.4K · 📥 6K · 📦 75K · 📋 1.9K - 21% open · ⏱️ 14.02.2025): ``` git clone https://github.com/RaRe-Technologies/gensim ``` - [PyPi](https://pypi.org/project/gensim) (📥 4.8M / month · 📦 1.4K · ⏱️ 19.07.2024): ``` pip install gensim ``` - [Conda](https://anaconda.org/conda-forge/gensim) (📥 1.6M · ⏱️ 22.04.2025): ``` conda install -c conda-forge gensim ``` </details> <details><summary><b><a href="https://github.com/gunthercox/ChatterBot">ChatterBot</a></b> (🥇38 · ⭐ 14K) - ChatterBot is a machine learning, conversational dialog engine for.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/gunthercox/ChatterBot) (👨‍💻 110 · 🔀 4.5K · 📦 6.3K · 📋 1.7K - 8% open · ⏱️ 08.04.2025): ``` git clone https://github.com/gunthercox/ChatterBot ``` - [PyPi](https://pypi.org/project/chatterbot) (📥 32K / month · 📦 18 · ⏱️ 05.04.2025): ``` pip install chatterbot ``` </details> <details><summary><b><a href="https://github.com/NVIDIA/NeMo">NeMo</a></b> (🥇38 · ⭐ 14K) - 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) (👨‍💻 410 · 🔀 2.8K · 📥 420K · 📦 21 · 📋 2.6K - 6% open · ⏱️ 24.04.2025): ``` git clone https://github.com/NVIDIA/NeMo ``` - [PyPi](https://pypi.org/project/nemo-toolkit) (📥 300K / month · 📦 14 · ⏱️ 21.04.2025): ``` pip install nemo-toolkit ``` </details> <details><summary><b><a href="https://github.com/google/sentencepiece">sentencepiece</a></b> (🥇38 · ⭐ 11K) - 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) (👨‍💻 92 · 🔀 1.2K · 📥 56K · 📦 110K · 📋 780 - 6% open · ⏱️ 26.02.2025): ``` git clone https://github.com/google/sentencepiece ``` - [PyPi](https://pypi.org/project/sentencepiece) (📥 28M / month · 📦 1.7K · ⏱️ 19.02.2024): ``` pip install sentencepiece ``` - [Conda](https://anaconda.org/conda-forge/sentencepiece) (📥 1.5M · ⏱️ 22.04.2025): ``` conda install -c conda-forge sentencepiece ``` </details> <details><summary><b><a href="https://github.com/sloria/TextBlob">TextBlob</a></b> (🥇38 · ⭐ 9.3K) - 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) (👨‍💻 37 · 🔀 1.2K · 📥 120 · 📦 55K · 📋 280 - 34% open · ⏱️ 22.04.2025): ``` git clone https://github.com/sloria/TextBlob ``` - [PyPi](https://pypi.org/project/textblob) (📥 1.3M / month · 📦 400 · ⏱️ 13.01.2025): ``` pip install textblob ``` - [Conda](https://anaconda.org/conda-forge/textblob) (📥 280K · ⏱️ 22.04.2025): ``` conda install -c conda-forge textblob ``` </details> <details><summary><b><a href="https://github.com/facebookresearch/fairseq">fairseq</a></b> (🥈37 · ⭐ 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) (👨‍💻 430 · 🔀 6.5K · 📥 400 · 📦 4.2K · 📋 4.4K - 30% open · ⏱️ 18.10.2024): ``` git clone https://github.com/facebookresearch/fairseq ``` - [PyPi](https://pypi.org/project/fairseq) (📥 94K / month · 📦 120 · ⏱️ 27.06.2022): ``` pip install fairseq ``` - [Conda](https://anaconda.org/conda-forge/fairseq) (📥 140K · ⏱️ 22.04.2025): ``` conda install -c conda-forge fairseq ``` </details> <details><summary><b><a href="https://github.com/tensorflow/text">TensorFlow Text</a></b> (🥈36 · ⭐ 1.3K) - 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) (👨‍💻 180 · 🔀 350 · 📦 9.1K · 📋 370 - 52% open · ⏱️ 24.03.2025): ``` git clone https://github.com/tensorflow/text ``` - [PyPi](https://pypi.org/project/tensorflow-text) (📥 7M / month · 📦 230 · ⏱️ 04.04.2025): ``` pip install tensorflow-text ``` </details> <details><summary><b><a href="https://github.com/JohnSnowLabs/spark-nlp">spark-nlp</a></b> (🥈35 · ⭐ 4K) - 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) (👨‍💻 110 · 🔀 720 · 📦 590 · 📋 930 - 5% open · ⏱️ 20.02.2025): ``` git clone https://github.com/JohnSnowLabs/spark-nlp ``` - [PyPi](https://pypi.org/project/spark-nlp) (📥 4.2M / month · 📦 37 · ⏱️ 30.01.2025): ``` pip install spark-nlp ``` </details> <details><summary><b><a href="https://github.com/qdrant/qdrant">qdrant</a></b> (🥈34 · ⭐ 23K) - 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) (👨‍💻 130 · 🔀 1.6K · 📥 380K · 📦 120 · 📋 1.5K - 23% open · ⏱️ 22.04.2025): ``` git clone https://github.com/qdrant/qdrant ``` </details> <details><summary><b><a href="https://github.com/stanfordnlp/stanza">stanza</a></b> (🥈33 · ⭐ 7.4K) - 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) (👨‍💻 69 · 🔀 900 · 📦 3.8K · 📋 920 - 10% open · ⏱️ 24.12.2024): ``` git clone https://github.com/stanfordnlp/stanza ``` - [PyPi](https://pypi.org/project/stanza) (📥 360K / month · 📦 200 · ⏱️ 24.12.2024): ``` pip install stanza ``` - [Conda](https://anaconda.org/stanfordnlp/stanza) (📥 8.6K · ⏱️ 25.03.2025): ``` conda install -c stanfordnlp stanza ``` </details> <details><summary><b><a href="https://github.com/OpenNMT/OpenNMT-py">OpenNMT</a></b> (🥈33 · ⭐ 6.9K · 💤) - Open Source Neural Machine Translation and (Large) 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/OpenNMT/OpenNMT-py) (👨‍💻 190 · 🔀 2.3K · 📦 330 · 📋 1.5K - 2% open · ⏱️ 27.06.2024): ``` git clone https://github.com/OpenNMT/OpenNMT-py ``` - [PyPi](https://pypi.org/project/OpenNMT-py) (📥 13K / month · 📦 23 · ⏱️ 18.03.2024): ``` pip install OpenNMT-py ``` </details> <details><summary><b><a href="https://github.com/jamesturk/jellyfish">jellyfish</a></b> (🥈33 · ⭐ 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) (👨‍💻 34 · 🔀 160 · 📦 14K · 📋 140 - 2% open · ⏱️ 31.03.2025): ``` git clone https://github.com/jamesturk/jellyfish ``` - [PyPi](https://pypi.org/project/jellyfish) (📥 7.5M / month · 📦 300 · ⏱️ 31.03.2025): ``` pip install jellyfish ``` - [Conda](https://anaconda.org/conda-forge/jellyfish) (📥 1.3M · ⏱️ 22.04.2025): ``` conda install -c conda-forge jellyfish ``` </details> <details><summary><b><a href="https://github.com/comet-ml/opik">Opik</a></b> (🥈32 · ⭐ 6.8K) - Debug, evaluate, and monitor your LLM applications, RAG systems, and.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/comet-ml/opik) (👨‍💻 50 · 🔀 490 · 📥 12 · 📦 6 · 📋 260 - 29% open · ⏱️ 24.04.2025): ``` git clone https://github.com/comet-ml/opik ``` - [PyPi](https://pypi.org/project/opik) (📥 210K / month · 📦 10 · ⏱️ 23.04.2025): ``` pip install opik ``` </details> <details><summary><b><a href="https://github.com/argilla-io/argilla">rubrix</a></b> (🥈32 · ⭐ 4.5K) - 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) (👨‍💻 110 · 🔀 420 · 📦 3K · 📋 2.2K - 2% open · ⏱️ 10.03.2025): ``` git clone https://github.com/recognai/rubrix ``` - [PyPi](https://pypi.org/project/rubrix) (📥 3.6K / month · ⏱️ 24.10.2022): ``` pip install rubrix ``` - [Conda](https://anaconda.org/conda-forge/rubrix) (📥 44K · ⏱️ 22.04.2025): ``` conda install -c conda-forge rubrix ``` </details> <details><summary><b><a href="https://github.com/pytorch/text">torchtext</a></b> (🥈32 · ⭐ 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) (👨‍💻 160 · 🔀 810 · 📋 850 - 39% open · ⏱️ 24.02.2025): ``` git clone https://github.com/pytorch/text ``` - [PyPi](https://pypi.org/project/torchtext) (📥 840K / month · 📦 280 · ⏱️ 24.04.2024): ``` pip install torchtext ``` </details> <details><summary><b><a href="https://github.com/snowballstem/snowball">snowballstemmer</a></b> (🥈32 · ⭐ 780) - Snowball compiler and stemming algorithms. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/snowballstem/snowball) (👨‍💻 35 · 🔀 170 · 📦 10 · 📋 110 - 22% open · ⏱️ 24.04.2025): ``` git clone https://github.com/snowballstem/snowball ``` - [PyPi](https://pypi.org/project/snowballstemmer) (📥 19M / month · 📦 450 · ⏱️ 16.11.2021): ``` pip install snowballstemmer ``` - [Conda](https://anaconda.org/conda-forge/snowballstemmer) (📥 9.6M · ⏱️ 22.04.2025): ``` conda install -c conda-forge snowballstemmer ``` </details> <details><summary><b><a href="https://github.com/deeppavlov/DeepPavlov">DeepPavlov</a></b> (🥈31 · ⭐ 6.9K) - 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) (👨‍💻 78 · 🔀 1.2K · 📦 430 · 📋 640 - 4% open · ⏱️ 26.11.2024): ``` git clone https://github.com/deepmipt/DeepPavlov ``` - [PyPi](https://pypi.org/project/deeppavlov) (📥 12K / month · 📦 4 · ⏱️ 12.08.2024): ``` pip install deeppavlov ``` </details> <details><summary><b><a href="https://github.com/rspeer/python-ftfy">ftfy</a></b> (🥈31 · ⭐ 3.9K) - 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) (👨‍💻 20 · 🔀 120 · 📥 59 · 📦 30K · 📋 150 - 6% open · ⏱️ 30.10.2024): ``` git clone https://github.com/rspeer/python-ftfy ``` - [PyPi](https://pypi.org/project/ftfy) (📥 6M / month · 📦 570 · ⏱️ 26.10.2024): ``` pip install ftfy ``` - [Conda](https://anaconda.org/conda-forge/ftfy) (📥 320K · ⏱️ 22.04.2025): ``` conda install -c conda-forge ftfy ``` </details> <details><summary><b><a href="https://github.com/dedupeio/dedupe">Dedupe</a></b> (🥈30 · ⭐ 4.3K) - 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) (👨‍💻 72 · 🔀 550 · 📦 360 · 📋 820 - 9% open · ⏱️ 01.11.2024): ``` git clone https://github.com/dedupeio/dedupe ``` - [PyPi](https://pypi.org/project/dedupe) (📥 92K / month · 📦 19 · ⏱️ 15.08.2024): ``` pip install dedupe ``` - [Conda](https://anaconda.org/conda-forge/dedupe) (📥 110K · ⏱️ 22.04.2025): ``` conda install -c conda-forge dedupe ``` </details> <details><summary><b><a href="https://github.com/miso-belica/sumy">Sumy</a></b> (🥈30 · ⭐ 3.6K · 💤) - 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) (👨‍💻 32 · 🔀 530 · 📦 3.9K · 📋 120 - 18% open · ⏱️ 16.05.2024): ``` git clone https://github.com/miso-belica/sumy ``` - [PyPi](https://pypi.org/project/sumy) (📥 120K / month · 📦 31 · ⏱️ 23.10.2022): ``` pip install sumy ``` - [Conda](https://anaconda.org/conda-forge/sumy) (📥 12K · ⏱️ 22.04.2025): ``` conda install -c conda-forge sumy ``` </details> <details><summary><b><a href="https://github.com/explosion/spacy-transformers">spacy-transformers</a></b> (🥈29 · ⭐ 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) (👨‍💻 23 · 🔀 170 · 📥 170 · 📦 2.2K · ⏱️ 06.02.2025): ``` git clone https://github.com/explosion/spacy-transformers ``` - [PyPi](https://pypi.org/project/spacy-transformers) (📥 220K / month · 📦 98 · ⏱️ 06.02.2025): ``` pip install spacy-transformers ``` - [Conda](https://anaconda.org/conda-forge/spacy-transformers) (📥 110K · ⏱️ 22.04.2025): ``` conda install -c conda-forge spacy-transformers ``` </details> <details><summary><b><a href="https://github.com/life4/textdistance">TextDistance</a></b> (🥈28 · ⭐ 3.5K) - 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) (👨‍💻 18 · 🔀 250 · 📥 1.1K · 📦 8.4K · ⏱️ 18.04.2025): ``` git clone https://github.com/life4/textdistance ``` - [PyPi](https://pypi.org/project/textdistance) (📥 1M / month · 📦 99 · ⏱️ 16.07.2024): ``` pip install textdistance ``` - [Conda](https://anaconda.org/conda-forge/textdistance) (📥 800K · ⏱️ 22.04.2025): ``` conda install -c conda-forge textdistance ``` </details> <details><summary><b><a href="https://github.com/allenai/scispacy">SciSpacy</a></b> (🥈28 · ⭐ 1.8K) - 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) (👨‍💻 37 · 🔀 230 · 📦 1.2K · 📋 320 - 10% open · ⏱️ 23.11.2024): ``` git clone https://github.com/allenai/scispacy ``` - [PyPi](https://pypi.org/project/scispacy) (📥 39K / month · 📦 34 · ⏱️ 27.10.2024): ``` pip install scispacy ``` </details> <details><summary><b><a href="https://github.com/dwyl/english-words">english-words</a></b> (🥉27 · ⭐ 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) (👨‍💻 34 · 🔀 1.9K · 📦 2 · 📋 160 - 74% open · ⏱️ 06.01.2025): ``` git clone https://github.com/dwyl/english-words ``` - [PyPi](https://pypi.org/project/english-words) (📥 63K / month · 📦 14 · ⏱️ 24.05.2023): ``` pip install english-words ``` </details> <details><summary><b><a href="https://github.com/DerwenAI/pytextrank">PyTextRank</a></b> (🥉27 · ⭐ 2.2K · 💤) - Python implementation of TextRank algorithms (textgraphs) for.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/DerwenAI/pytextrank) (👨‍💻 19 · 🔀 340 · 📦 840 · 📋 100 - 12% open · ⏱️ 21.05.2024): ``` git clone https://github.com/DerwenAI/pytextrank ``` - [PyPi](https://pypi.org/project/pytextrank) (📥 73K / month · 📦 19 · ⏱️ 21.02.2024): ``` pip install pytextrank ``` </details> <details><summary><b><a href="https://github.com/cltk/cltk">CLTK</a></b> (🥉27 · ⭐ 850) - The Classical Language Toolkit. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/cltk/cltk) (👨‍💻 120 · 🔀 330 · 📥 130 · 📦 300 · 📋 580 - 6% open · ⏱️ 01.12.2024): ``` git clone https://github.com/cltk/cltk ``` - [PyPi](https://pypi.org/project/cltk) (📥 7K / month · 📦 17 · ⏱️ 01.12.2024): ``` pip install cltk ``` </details> <details><summary><b><a href="https://github.com/zjunlp/DeepKE">DeepKE</a></b> (🥉26 · ⭐ 3.9K) - [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) (👨‍💻 33 · 🔀 710 · 📦 24 · 📋 610 - 1% open · ⏱️ 22.04.2025): ``` git clone https://github.com/zjunlp/deepke ``` - [PyPi](https://pypi.org/project/deepke) (📥 2K / month · ⏱️ 21.09.2023): ``` pip install deepke ``` </details> <details><summary><b><a href="https://github.com/JasonKessler/scattertext">scattertext</a></b> (🥉26 · ⭐ 2.3K · 💤) - Beautiful visualizations of how language differs among.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/JasonKessler/scattertext) (👨‍💻 14 · 🔀 290 · 📦 660 · 📋 100 - 22% open · ⏱️ 23.09.2024): ``` git clone https://github.com/JasonKessler/scattertext ``` - [PyPi](https://pypi.org/project/scattertext) (📥 11K / month · 📦 5 · ⏱️ 23.09.2024): ``` pip install scattertext ``` - [Conda](https://anaconda.org/conda-forge/scattertext) (📥 110K · ⏱️ 22.04.2025): ``` conda install -c conda-forge scattertext ``` </details> <details><summary><b><a href="https://github.com/explosion/sense2vec">sense2vec</a></b> (🥉24 · ⭐ 1.6K) - Contextually-keyed word vectors. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/explosion/sense2vec) (👨‍💻 20 · 🔀 240 · 📥 72K · 📦 460 · 📋 120 - 20% open · ⏱️ 23.04.2025): ``` git clone https://github.com/explosion/sense2vec ``` - [PyPi](https://pypi.org/project/sense2vec) (📥 2.7K / month · 📦 13 · ⏱️ 19.04.2021): ``` pip install sense2vec ``` - [Conda](https://anaconda.org/conda-forge/sense2vec) (📥 59K · ⏱️ 22.04.2025): ``` conda install -c conda-forge sense2vec ``` </details> <details><summary><b><a href="https://github.com/unitaryai/detoxify">detoxify</a></b> (🥉24 · ⭐ 1K) - Trained models & code to predict toxic comments on all 3 Jigsaw Toxic.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/unitaryai/detoxify) (👨‍💻 14 · 🔀 120 · 📥 1.1M · 📦 870 · 📋 67 - 55% open · ⏱️ 07.03.2025): ``` git clone https://github.com/unitaryai/detoxify ``` - [PyPi](https://pypi.org/project/detoxify) (📥 120K / month · 📦 30 · ⏱️ 01.02.2024): ``` pip install detoxify ``` </details> <details><summary><b><a href="https://github.com/google-research/text-to-text-transfer-transformer">T5</a></b> (🥉23 · ⭐ 6.3K) - 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) (👨‍💻 60 · 🔀 760 · 📋 450 - 23% open · ⏱️ 27.02.2025): ``` git clone https://github.com/google-research/text-to-text-transfer-transformer ``` - [PyPi](https://pypi.org/project/t5) (📥 51K / month · 📦 2 · ⏱️ 18.10.2021): ``` pip install t5 ``` </details> <details><summary><b><a href="https://github.com/awslabs/sockeye">Sockeye</a></b> (🥉22 · ⭐ 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) (👨‍💻 60 · 🔀 320 · 📥 21 · 📋 310 - 3% open · ⏱️ 24.10.2024): ``` git clone https://github.com/awslabs/sockeye ``` - [PyPi](https://pypi.org/project/sockeye) (📥 2.8K / month · ⏱️ 03.03.2023): ``` pip install sockeye ``` </details> <details><summary><b><a href="https://github.com/IndicoDataSolutions/finetune">finetune</a></b> (🥉22 · ⭐ 710) - 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) (👨‍💻 24 · 🔀 78 · 📦 14 · 📋 140 - 15% open · ⏱️ 31.03.2025): ``` git clone https://github.com/IndicoDataSolutions/finetune ``` - [PyPi](https://pypi.org/project/finetune) (📥 750 / month · 📦 2 · ⏱️ 29.09.2023): ``` pip install finetune ``` </details> <details><summary><b><a href="https://github.com/webis-de/small-text">small-text</a></b> (🥉22 · ⭐ 610) - 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) (👨‍💻 9 · 🔀 70 · 📦 34 · 📋 66 - 27% open · ⏱️ 06.04.2025): ``` git clone https://github.com/webis-de/small-text ``` - [PyPi](https://pypi.org/project/small-text) (📥 1.3K / month · ⏱️ 06.04.2025): ``` pip install small-text ``` - [Conda](https://anaconda.org/conda-forge/small-text) (📥 14K · ⏱️ 22.04.2025): ``` conda install -c conda-forge small-text ``` </details> <details><summary><b><a href="https://github.com/EricFillion/happy-transformer">happy-transformer</a></b> (🥉22 · ⭐ 530) - 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) (👨‍💻 14 · 🔀 68 · 📦 320 · 📋 130 - 16% open · ⏱️ 22.03.2025): ``` git clone https://github.com/EricFillion/happy-transformer ``` - [PyPi](https://pypi.org/project/happytransformer) (📥 3.1K / month · 📦 5 · ⏱️ 05.08.2023): ``` pip install happytransformer ``` </details> <details><summary><b><a href="https://github.com/utterworks/fast-bert">fast-bert</a></b> (🥉21 · ⭐ 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) (👨‍💻 37 · 🔀 340 · 📋 260 - 63% open · ⏱️ 19.08.2024): ``` git clone https://github.com/utterworks/fast-bert ``` - [PyPi](https://pypi.org/project/fast-bert) (📥 2.5K / month · ⏱️ 19.08.2024): ``` pip install fast-bert ``` </details> <details><summary><b><a href="https://github.com/unum-cloud/uform">UForm</a></b> (🥉21 · ⭐ 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) (👨‍💻 19 · 🔀 64 · 📥 600 · 📦 34 · 📋 34 - 35% open · ⏱️ 03.01.2025): ``` git clone https://github.com/unum-cloud/uform ``` - [PyPi](https://pypi.org/project/uform) (📥 1.2K / month · 📦 2 · ⏱️ 03.01.2025): ``` pip install uform ``` </details> <details><summary><b><a href="https://github.com/facebookresearch/vizseq">VizSeq</a></b> (🥉16 · ⭐ 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) (👨‍💻 4 · 🔀 61 · 📦 12 · 📋 16 - 43% open · ⏱️ 07.03.2025): ``` git clone https://github.com/facebookresearch/vizseq ``` - [PyPi](https://pypi.org/project/vizseq) (📥 290 / month · ⏱️ 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> (🥈37 · ⭐ 12K · 💀) - 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/facebookresearch/fastText">fastText</a></b> (🥈35 · ⭐ 26K · 💀) - Library for fast text representation and classification. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/facebookresearch/ParlAI">ParlAI</a></b> (🥈32 · ⭐ 11K · 💀) - 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> (🥈32 · ⭐ 9.3K · 💀) - Fuzzy String Matching in Python. <code><a href="http://bit.ly/2KucAZR">❗️GPL-2.0</a></code> - <b><a href="https://github.com/makcedward/nlpaug">nlpaug</a></b> (🥈30 · ⭐ 4.6K · 💀) - Data augmentation for NLP. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/saffsd/langid.py">langid</a></b> (🥈29 · ⭐ 2.4K · 💀) - Stand-alone language identification system. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> - <b><a href="https://github.com/bee-san/Ciphey">Ciphey</a></b> (🥈28 · ⭐ 19K · 💀) - 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> (🥈28 · ⭐ 4.7K · 💀) - VADER Sentiment Analysis. VADER (Valence Aware Dictionary.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/fastnlp/fastNLP">fastNLP</a></b> (🥈28 · ⭐ 3.1K · 💀) - 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/dmlc/gluon-nlp">GluonNLP</a></b> (🥈28 · ⭐ 2.6K · 💀) - 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/chartbeat-labs/textacy">textacy</a></b> (🥈28 · ⭐ 2.2K · 💀) - NLP, before and after spaCy. <code>❗Unlicensed</code> - <b><a href="https://github.com/vi3k6i5/flashtext">flashtext</a></b> (🥉27 · ⭐ 5.6K · 💀) - 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/nipunsadvilkar/pySBD">pySBD</a></b> (🥉27 · ⭐ 850 · 💀) - 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/huggingface/neuralcoref">neuralcoref</a></b> (🥉26 · ⭐ 2.9K · 💀) - Fast Coreference Resolution in spaCy with Neural Networks. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/aboSamoor/polyglot">polyglot</a></b> (🥉26 · ⭐ 2.3K · 💀) - Multilingual text (NLP) processing toolkit. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/undertheseanlp/underthesea">underthesea</a></b> (🥉26 · ⭐ 1.5K) - Underthesea - Vietnamese NLP Toolkit. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/facebookresearch/pytext">PyText</a></b> (🥉25 · ⭐ 6.3K · 💀) - 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/snipsco/snips-nlu">Snips NLU</a></b> (🥉25 · ⭐ 3.9K · 💀) - 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/PetrochukM/PyTorch-NLP">pytorch-nlp</a></b> (🥉25 · ⭐ 2.2K · 💀) - 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/minimaxir/textgenrnn">textgenrnn</a></b> (🥉24 · ⭐ 4.9K · 💀) - 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/thunlp/OpenPrompt">OpenPrompt</a></b> (🥉24 · ⭐ 4.6K · 💀) - An Open-Source Framework for Prompt-Learning. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/NTMC-Community/MatchZoo">MatchZoo</a></b> (🥉24 · ⭐ 3.9K · 💀) - 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> (🥉24 · ⭐ 2.8K · 💀) - 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> (🥉24 · ⭐ 2.4K · 💀) - 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/deepset-ai/FARM">FARM</a></b> (🥉24 · ⭐ 1.8K · 💀) - 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/VKCOM/YouTokenToMe">YouTokenToMe</a></b> (🥉24 · ⭐ 960 · 💀) - 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> (🥉24 · ⭐ 620 · 💀) - Pure-Python full-text search library. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">❗️BSD-1-Clause</a></code> - <b><a href="https://github.com/asyml/texar">Texar</a></b> (🥉23 · ⭐ 2.4K · 💀) - 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/nyu-mll/jiant">jiant</a></b> (🥉23 · ⭐ 1.7K · 💀) - jiant is an nlp toolkit. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/minimaxir/gpt-2-simple">gpt-2-simple</a></b> (🥉22 · ⭐ 3.4K · 💀) - 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> (🥉22 · ⭐ 2.9K · 💀) - 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> (🥉22 · ⭐ 2.9K · 💀) - Text preprocessing, representation and visualization from zero to.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/Alir3z4/python-stop-words">stop-words</a></b> (🥉22 · ⭐ 160 · 💀) - 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/Delta-ML/delta">DELTA</a></b> (🥉21 · ⭐ 1.6K · 💀) - 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/Hironsan/anago">anaGo</a></b> (🥉21 · ⭐ 1.5K · 💀) - 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/textpipe/textpipe">textpipe</a></b> (🥉21 · ⭐ 300 · 💀) - Textpipe: clean and extract metadata from text. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/anhaidgroup/deepmatcher">DeepMatcher</a></b> (🥉20 · ⭐ 5.2K · 💀) - 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> (🥉20 · ⭐ 3.3K · 💀) - 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/vrasneur/pyfasttext">pyfasttext</a></b> (🥉20 · ⭐ 230 · 💀) - Yet another Python binding for fastText. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/PKSHATechnology-Research/camphr">Camphr</a></b> (🥉19 · ⭐ 340 · 💀) - 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/jaidevd/numerizer">numerizer</a></b> (🥉19 · ⭐ 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/Franck-Dernoncourt/NeuroNER">NeuroNER</a></b> (🥉18 · ⭐ 1.7K · 💀) - 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> (🥉18 · ⭐ 680 · 💀) - 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> (🥉18 · ⭐ 580 · 💀) - 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> (🥉18 · ⭐ 420 · 💀) - TextAugment: Text Augmentation Library. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/thunlp/OpenNRE">OpenNRE</a></b> (🥉16 · ⭐ 4.4K · 💀) - An Open-Source Package for Neural Relation Extraction (NRE). <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/RUCAIBox/TextBox">TextBox</a></b> (🥉16 · ⭐ 1.1K · 💀) - 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/pytorch/translate">Translate</a></b> (🥉16 · ⭐ 830 · 💀) - 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/shaypal5/skift">skift</a></b> (🥉16 · ⭐ 240 · 💀) - 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/facebookresearch/BLINK">BLINK</a></b> (🥉15 · ⭐ 1.2K · 💀) - Entity Linker solution. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/abelriboulot/onnxt5">ONNX-T5</a></b> (🥉15 · ⭐ 250 · 💀) - Summarization, translation, sentiment-analysis, text-generation.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/victordibia/neuralqa">NeuralQA</a></b> (🥉15 · ⭐ 230 · 💀) - 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/spring-media/headliner">Headliner</a></b> (🥉15 · ⭐ 230 · 💀) - Easy training and deployment of seq2seq models. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/feedly/transfer-nlp">TransferNLP</a></b> (🥉14 · ⭐ 290 · 💀) - 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> (🥉13 · ⭐ 190 · 💀) - 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> (🥉12 · ⭐ 110 · 💀) - 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> (🥇48 · ⭐ 13K) - Python Imaging Library (Fork). <code><a href="https://tldrlegal.com/search?q=PIL">❗️PIL</a></code></summary> - [GitHub](https://github.com/python-pillow/Pillow) (👨‍💻 480 · 🔀 2.3K · 📦 2.2M · 📋 3.3K - 3% open · ⏱️ 21.04.2025): ``` git clone https://github.com/python-pillow/Pillow ``` - [PyPi](https://pypi.org/project/Pillow) (📥 140M / month · 📦 14K · ⏱️ 12.04.2025): ``` pip install Pillow ``` - [Conda](https://anaconda.org/conda-forge/pillow) (📥 53M · ⏱️ 22.04.2025): ``` conda install -c conda-forge pillow ``` </details> <details><summary><b><a href="https://github.com/pytorch/vision">torchvision</a></b> (🥇42 · ⭐ 17K) - 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) (👨‍💻 640 · 🔀 7K · 📥 40K · 📦 21 · 📋 3.7K - 29% open · ⏱️ 23.04.2025): ``` git clone https://github.com/pytorch/vision ``` - [PyPi](https://pypi.org/project/torchvision) (📥 17M / month · 📦 7K · ⏱️ 23.04.2025): ``` pip install torchvision ``` - [Conda](https://anaconda.org/conda-forge/torchvision) (📥 2.6M · ⏱️ 22.04.2025): ``` conda install -c conda-forge torchvision ``` </details> <details><summary><b><a href="https://github.com/huggingface/pytorch-image-models">PyTorch Image Models</a></b> (🥇41 · ⭐ 34K · 📉) - 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) (👨‍💻 170 · 🔀 4.9K · 📥 7.7M · 📦 54K · 📋 970 - 5% open · ⏱️ 22.04.2025): ``` git clone https://github.com/rwightman/pytorch-image-models ``` - [PyPi](https://pypi.org/project/timm) (📥 6.9M / month · 📦 1.1K · ⏱️ 23.02.2025): ``` pip install timm ``` - [Conda](https://anaconda.org/conda-forge/timm) (📥 370K · ⏱️ 22.04.2025): ``` conda install -c conda-forge timm ``` </details> <details><summary><b><a href="https://github.com/albumentations-team/albumentations">Albumentations</a></b> (🥇41 · ⭐ 15K) - 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) (👨‍💻 170 · 🔀 1.7K · 📦 36K · 📋 1.2K - 18% open · ⏱️ 24.04.2025): ``` git clone https://github.com/albumentations-team/albumentations ``` - [PyPi](https://pypi.org/project/albumentations) (📥 6.6M / month · 📦 660 · ⏱️ 28.02.2025): ``` pip install albumentations ``` - [Conda](https://anaconda.org/conda-forge/albumentations) (📥 270K · ⏱️ 22.04.2025): ``` conda install -c conda-forge albumentations ``` </details> <details><summary><b><a href="https://github.com/Zulko/moviepy">MoviePy</a></b> (🥇41 · ⭐ 13K) - Video editing with Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/Zulko/moviepy) (👨‍💻 180 · 🔀 1.7K · 📦 60K · 📋 2K - 23% open · ⏱️ 06.02.2025): ``` git clone https://github.com/Zulko/moviepy ``` - [PyPi](https://pypi.org/project/moviepy) (📥 3M / month · 📦 1K · ⏱️ 10.01.2025): ``` pip install moviepy ``` - [Conda](https://anaconda.org/conda-forge/moviepy) (📥 300K · ⏱️ 22.04.2025): ``` conda install -c conda-forge moviepy ``` </details> <details><summary><b><a href="https://github.com/serengil/deepface">deepface</a></b> (🥇39 · ⭐ 19K) - 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) (👨‍💻 87 · 🔀 2.5K · 📦 7K · 📋 1.2K - 0% open · ⏱️ 19.04.2025): ``` git clone https://github.com/serengil/deepface ``` - [PyPi](https://pypi.org/project/deepface) (📥 660K / month · 📦 44 · ⏱️ 17.08.2024): ``` pip install deepface ``` </details> <details><summary><b><a href="https://github.com/deepinsight/insightface">InsightFace</a></b> (🥈38 · ⭐ 25K) - 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) (👨‍💻 66 · 🔀 5.5K · 📥 7.6M · 📦 4K · 📋 2.6K - 45% open · ⏱️ 23.04.2025): ``` git clone https://github.com/deepinsight/insightface ``` - [PyPi](https://pypi.org/project/insightface) (📥 240K / month · 📦 30 · ⏱️ 17.12.2022): ``` pip install insightface ``` </details> <details><summary><b><a href="https://github.com/kornia/kornia">Kornia</a></b> (🥈37 · ⭐ 10K) - 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) (👨‍💻 280 · 🔀 980 · 📥 1.8K · 📦 15K · 📋 970 - 30% open · ⏱️ 22.04.2025): ``` git clone https://github.com/kornia/kornia ``` - [PyPi](https://pypi.org/project/kornia) (📥 2.4M / month · 📦 310 · ⏱️ 11.01.2025): ``` pip install kornia ``` - [Conda](https://anaconda.org/conda-forge/kornia) (📥 220K · ⏱️ 22.04.2025): ``` conda install -c conda-forge kornia ``` </details> <details><summary><b><a href="https://github.com/imageio/imageio">imageio</a></b> (🥈37 · ⭐ 1.6K) - 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) (👨‍💻 120 · 🔀 310 · 📥 1.6K · 📦 170K · 📋 610 - 16% open · ⏱️ 21.02.2025): ``` git clone https://github.com/imageio/imageio ``` - [PyPi](https://pypi.org/project/imageio) (📥 26M / month · 📦 2.6K · ⏱️ 20.01.2025): ``` pip install imageio ``` - [Conda](https://anaconda.org/conda-forge/imageio) (📥 7.8M · ⏱️ 22.04.2025): ``` conda install -c conda-forge imageio ``` </details> <details><summary><b><a href="https://github.com/opencv/opencv-python">opencv-python</a></b> (🥈35 · ⭐ 4.8K) - 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) (👨‍💻 53 · 🔀 870 · 📦 560K · 📋 840 - 16% open · ⏱️ 16.01.2025): ``` git clone https://github.com/opencv/opencv-python ``` - [PyPi](https://pypi.org/project/opencv-python) (📥 17M / month · 📦 12K · ⏱️ 16.01.2025): ``` pip install opencv-python ``` </details> <details><summary><b><a href="https://github.com/emcconville/wand">Wand</a></b> (🥈34 · ⭐ 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) (👨‍💻 110 · 🔀 200 · 📥 52K · 📦 21K · 📋 430 - 6% open · ⏱️ 01.04.2025): ``` git clone https://github.com/emcconville/wand ``` - [PyPi](https://pypi.org/project/wand) (📥 1.1M / month · 📦 260 · ⏱️ 03.11.2023): ``` pip install wand ``` - [Conda](https://anaconda.org/conda-forge/wand) (📥 130K · ⏱️ 22.04.2025): ``` conda install -c conda-forge wand ``` </details> <details><summary><b><a href="https://github.com/facebookresearch/detectron2">detectron2</a></b> (🥈33 · ⭐ 32K) - 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) (👨‍💻 280 · 🔀 7.5K · 📦 2.4K · 📋 3.6K - 14% open · ⏱️ 13.04.2025): ``` git clone https://github.com/facebookresearch/detectron2 ``` - [PyPi](https://pypi.org/project/detectron2) (📦 13 · ⏱️ 06.02.2020): ``` pip install detectron2 ``` - [Conda](https://anaconda.org/conda-forge/detectron2) (📥 660K · ⏱️ 22.04.2025): ``` conda install -c conda-forge detectron2 ``` </details> <details><summary><b><a href="https://github.com/PaddlePaddle/PaddleSeg">PaddleSeg</a></b> (🥈33 · ⭐ 9K) - 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) (👨‍💻 130 · 🔀 1.7K · 📦 1.4K · 📋 2.2K - 0% open · ⏱️ 25.12.2024): ``` git clone https://github.com/PaddlePaddle/PaddleSeg ``` - [PyPi](https://pypi.org/project/paddleseg) (📥 2K / month · 📦 7 · ⏱️ 30.11.2022): ``` pip install paddleseg ``` </details> <details><summary><b><a href="https://github.com/JohannesBuchner/imagehash">ImageHash</a></b> (🥈31 · ⭐ 3.6K) - A Python Perceptual Image Hashing Module. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary> - [GitHub](https://github.com/JohannesBuchner/imagehash) (👨‍💻 28 · 🔀 340 · 📦 17K · 📋 150 - 15% open · ⏱️ 17.04.2025): ``` git clone https://github.com/JohannesBuchner/imagehash ``` - [PyPi](https://pypi.org/project/ImageHash) (📥 1.8M / month · 📦 270 · ⏱️ 01.02.2025): ``` pip install ImageHash ``` - [Conda](https://anaconda.org/conda-forge/imagehash) (📥 440K · ⏱️ 22.04.2025): ``` conda install -c conda-forge imagehash ``` </details> <details><summary><b><a href="https://github.com/lightly-ai/lightly">lightly</a></b> (🥈31 · ⭐ 3.4K) - 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) (👨‍💻 65 · 🔀 290 · 📦 430 · 📋 600 - 12% open · ⏱️ 22.04.2025): ``` git clone https://github.com/lightly-ai/lightly ``` - [PyPi](https://pypi.org/project/lightly) (📥 56K / month · 📦 20 · ⏱️ 22.04.2025): ``` pip install lightly ``` </details> <details><summary><b><a href="https://github.com/lucidrains/vit-pytorch">vit-pytorch</a></b> (🥈30 · ⭐ 23K) - 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) (👨‍💻 23 · 🔀 3.2K · 📦 640 · 📋 280 - 49% open · ⏱️ 05.03.2025): ``` git clone https://github.com/lucidrains/vit-pytorch ``` - [PyPi](https://pypi.org/project/vit-pytorch) (📥 26K / month · 📦 17 · ⏱️ 05.03.2025): ``` pip install vit-pytorch ``` </details> <details><summary><b><a href="https://github.com/PaddlePaddle/PaddleDetection">PaddleDetection</a></b> (🥈30 · ⭐ 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) (👨‍💻 190 · 🔀 2.9K · 📋 5.8K - 21% open · ⏱️ 16.04.2025): ``` git clone https://github.com/PaddlePaddle/PaddleDetection ``` - [PyPi](https://pypi.org/project/paddledet) (📥 1.4K / month · 📦 2 · ⏱️ 19.09.2022): ``` pip install paddledet ``` </details> <details><summary><b><a href="https://github.com/obss/sahi">sahi</a></b> (🥈30 · ⭐ 4.5K) - 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) (👨‍💻 51 · 🔀 630 · 📥 36K · 📦 1.8K · ⏱️ 16.04.2025): ``` git clone https://github.com/obss/sahi ``` - [PyPi](https://pypi.org/project/sahi) (📥 150K / month · 📦 33 · ⏱️ 09.03.2025): ``` pip install sahi ``` - [Conda](https://anaconda.org/conda-forge/sahi) (📥 96K · ⏱️ 22.04.2025): ``` conda install -c conda-forge sahi ``` </details> <details><summary><b><a href="https://github.com/mindee/doctr">doctr</a></b> (🥉29 · ⭐ 4.6K) - 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) (👨‍💻 63 · 🔀 490 · 📥 5.3M · 📋 400 - 6% open · ⏱️ 23.04.2025): ``` git clone https://github.com/mindee/doctr ``` - [PyPi](https://pypi.org/project/python-doctr) (📥 100K / month · 📦 14 · ⏱️ 30.01.2025): ``` pip install python-doctr ``` </details> <details><summary><b><a href="https://github.com/1adrianb/face-alignment">Face Alignment</a></b> (🥉28 · ⭐ 7.3K · 💤) - 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) (👨‍💻 26 · 🔀 1.4K · 📦 21 · 📋 320 - 24% open · ⏱️ 30.08.2024): ``` git clone https://github.com/1adrianb/face-alignment ``` - [PyPi](https://pypi.org/project/face-alignment) (📥 67K / month · 📦 10 · ⏱️ 17.08.2023): ``` pip install face-alignment ``` </details> <details><summary><b><a href="https://github.com/abhiTronix/vidgear">vidgear</a></b> (🥉28 · ⭐ 3.5K · 💤) - A High-performance cross-platform Video Processing Python.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/abhiTronix/vidgear) (👨‍💻 14 · 🔀 260 · 📥 2.3K · 📦 720 · 📋 300 - 2% open · ⏱️ 22.06.2024): ``` git clone https://github.com/abhiTronix/vidgear ``` - [PyPi](https://pypi.org/project/vidgear) (📥 20K / month · 📦 15 · ⏱️ 22.06.2024): ``` pip install vidgear ``` </details> <details><summary><b><a href="https://github.com/ipazc/mtcnn">mtcnn</a></b> (🥉28 · ⭐ 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) (👨‍💻 16 · 🔀 530 · 📥 50 · 📦 8.3K · 📋 130 - 37% open · ⏱️ 08.10.2024): ``` git clone https://github.com/ipazc/mtcnn ``` - [PyPi](https://pypi.org/project/mtcnn) (📥 170K / month · 📦 73 · ⏱️ 08.10.2024): ``` pip install mtcnn ``` - [Conda](https://anaconda.org/conda-forge/mtcnn) (📥 15K · ⏱️ 22.04.2025): ``` conda install -c conda-forge mtcnn ``` </details> <details><summary><b><a href="https://github.com/timesler/facenet-pytorch">facenet-pytorch</a></b> (🥉27 · ⭐ 4.8K · 💤) - 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) (👨‍💻 18 · 🔀 940 · 📥 1.7M · 📦 3.3K · 📋 190 - 41% open · ⏱️ 02.08.2024): ``` git clone https://github.com/timesler/facenet-pytorch ``` - [PyPi](https://pypi.org/project/facenet-pytorch) (📥 130K / month · 📦 51 · ⏱️ 29.04.2024): ``` pip install facenet-pytorch ``` </details> <details><summary><b><a href="https://github.com/CellProfiler/CellProfiler">CellProfiler</a></b> (🥉27 · ⭐ 970) - 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) (👨‍💻 150 · 🔀 390 · 📥 8.6K · 📦 28 · 📋 3.3K - 9% open · ⏱️ 22.04.2025): ``` git clone https://github.com/CellProfiler/CellProfiler ``` - [PyPi](https://pypi.org/project/cellprofiler) (📥 1.2K / month · 📦 2 · ⏱️ 16.09.2024): ``` pip install cellprofiler ``` </details> <details><summary><b><a href="https://github.com/luispedro/mahotas">mahotas</a></b> (🥉27 · ⭐ 860) - Computer Vision in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/luispedro/mahotas) (👨‍💻 35 · 🔀 150 · 📦 1.5K · 📋 92 - 22% open · ⏱️ 25.02.2025): ``` git clone https://github.com/luispedro/mahotas ``` - [PyPi](https://pypi.org/project/mahotas) (📥 23K / month · 📦 63 · ⏱️ 17.07.2024): ``` pip install mahotas ``` - [Conda](https://anaconda.org/conda-forge/mahotas) (📥 620K · ⏱️ 22.04.2025): ``` conda install -c conda-forge mahotas ``` </details> <details><summary><b><a href="https://github.com/tryolabs/norfair">Norfair</a></b> (🥉26 · ⭐ 2.5K · 💤) - Lightweight Python library for adding real-time multi-object.. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/tryolabs/norfair) (👨‍💻 31 · 🔀 260 · 📥 340 · 📦 300 · 📋 170 - 14% open · ⏱️ 27.07.2024): ``` git clone https://github.com/tryolabs/norfair ``` - [PyPi](https://pypi.org/project/norfair) (📥 28K / month · 📦 9 · ⏱️ 30.05.2022): ``` pip install norfair ``` </details> <details><summary><b><a href="https://github.com/libvips/pyvips">pyvips</a></b> (🥉26 · ⭐ 690) - python binding for libvips using cffi. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/libvips/pyvips) (👨‍💻 16 · 🔀 50 · 📦 1K · 📋 460 - 42% open · ⏱️ 19.04.2025): ``` git clone https://github.com/libvips/pyvips ``` - [PyPi](https://pypi.org/project/pyvips) (📥 86K / month · 📦 77 · ⏱️ 28.04.2024): ``` pip install pyvips ``` - [Conda](https://anaconda.org/conda-forge/pyvips) (📥 210K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pyvips ``` </details> <details><summary><b><a href="https://github.com/facebookresearch/mmf">MMF</a></b> (🥉25 · ⭐ 5.6K) - 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) (👨‍💻 120 · 🔀 920 · 📦 21 · 📋 690 - 21% open · ⏱️ 24.04.2025): ``` git clone https://github.com/facebookresearch/mmf ``` - [PyPi](https://pypi.org/project/mmf) (📥 850 / month · 📦 1 · ⏱️ 12.06.2020): ``` pip install mmf ``` </details> <details><summary><b><a href="https://github.com/idealo/imagededup">Image Deduplicator</a></b> (🥉24 · ⭐ 5.3K) - 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) (👨‍💻 17 · 🔀 460 · 📦 180 · 📋 130 - 32% open · ⏱️ 19.03.2025): ``` git clone https://github.com/idealo/imagededup ``` - [PyPi](https://pypi.org/project/imagededup) (📥 23K / month · 📦 5 · ⏱️ 28.04.2023): ``` pip install imagededup ``` </details> <details><summary><b><a href="https://github.com/qubvel/segmentation_models">segmentation_models</a></b> (🥉24 · ⭐ 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) (👨‍💻 15 · 🔀 1K · 📋 540 - 50% open · ⏱️ 21.08.2024): ``` git clone https://github.com/qubvel/segmentation_models ``` - [PyPi](https://pypi.org/project/segmentation_models) (📥 27K / month · 📦 28 · ⏱️ 10.01.2020): ``` pip install segmentation_models ``` </details> <details><summary><b><a href="https://github.com/facebookresearch/pytorchvideo">pytorchvideo</a></b> (🥉24 · ⭐ 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) (👨‍💻 58 · 🔀 410 · 📋 210 - 50% open · ⏱️ 25.01.2025): ``` git clone https://github.com/facebookresearch/pytorchvideo ``` - [PyPi](https://pypi.org/project/pytorchvideo) (📥 58K / month · 📦 24 · ⏱️ 20.01.2022): ``` pip install pytorchvideo ``` </details> <details><summary><b><a href="https://github.com/tensorflow/graphics">tensorflow-graphics</a></b> (🥉24 · ⭐ 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) (👨‍💻 39 · 🔀 370 · 📋 240 - 60% open · ⏱️ 03.02.2025): ``` git clone https://github.com/tensorflow/graphics ``` - [PyPi](https://pypi.org/project/tensorflow-graphics) (📥 24K / month · 📦 11 · ⏱️ 03.12.2021): ``` pip install tensorflow-graphics ``` </details> <details><summary><b><a href="https://github.com/libffcv/ffcv">ffcv</a></b> (🥉23 · ⭐ 2.9K · 💤) - 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) (👨‍💻 31 · 🔀 180 · 📦 69 · 📋 290 - 38% open · ⏱️ 06.05.2024): ``` git clone https://github.com/libffcv/ffcv ``` - [PyPi](https://pypi.org/project/ffcv) (📥 780 / month · 📦 1 · ⏱️ 28.01.2022): ``` pip install ffcv ``` </details> <details><summary><b><a href="https://github.com/google-research/kubric">kubric</a></b> (🥉23 · ⭐ 2.5K) - 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) (👨‍💻 31 · 🔀 240 · 📦 7 · 📋 190 - 33% open · ⏱️ 18.03.2025): ``` git clone https://github.com/google-research/kubric ``` - [PyPi](https://pypi.org/project/kubric-nightly) (📥 22K / month · ⏱️ 27.12.2023): ``` pip install kubric-nightly ``` </details> <details><summary><b><a href="https://github.com/airctic/icevision">icevision</a></b> (🥉22 · ⭐ 860) - 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) (👨‍💻 41 · 🔀 130 · 📋 570 - 10% open · ⏱️ 31.10.2024): ``` git clone https://github.com/airctic/icevision ``` - [PyPi](https://pypi.org/project/icevision) (📥 4.2K / month · 📦 6 · ⏱️ 10.02.2022): ``` pip install icevision ``` </details> <details><summary><b><a href="https://github.com/facebookresearch/SlowFast">PySlowFast</a></b> (🥉21 · ⭐ 6.9K) - 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) (👨‍💻 34 · 🔀 1.2K · 📦 23 · 📋 710 - 58% open · ⏱️ 26.11.2024): ``` git clone https://github.com/facebookresearch/SlowFast ``` - [PyPi](https://pypi.org/project/pyslowfast) (📥 44 / month · ⏱️ 15.01.2020): ``` pip install pyslowfast ``` </details> <details><summary><b><a href="https://github.com/idealo/image-super-resolution">Image Super-Resolution</a></b> (🥉21 · ⭐ 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) (👨‍💻 11 · 🔀 750 · 📋 220 - 48% open · ⏱️ 18.12.2024): ``` git clone https://github.com/idealo/image-super-resolution ``` - [PyPi](https://pypi.org/project/ISR) (📥 6.7K / month · 📦 5 · ⏱️ 08.01.2020): ``` pip install ISR ``` - [Docker Hub](https://hub.docker.com/r/idealo/image-super-resolution-gpu) (📥 280 · ⭐ 1 · ⏱️ 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> (🥉17 · ⭐ 3.5K) - 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) (👨‍💻 93 · 🔀 450 · 📋 270 - 56% open · ⏱️ 15.04.2025): ``` git clone https://github.com/google-research/scenic ``` </details> <details><summary>Show 26 hidden projects...</summary> - <b><a href="https://github.com/scikit-image/scikit-image">scikit-image</a></b> (🥇42 · ⭐ 6.2K) - Image processing in Python. <code>❗Unlicensed</code> - <b><a href="https://github.com/aleju/imgaug">imgaug</a></b> (🥈37 · ⭐ 15K · 💀) - Image augmentation for machine learning experiments. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/glfw/glfw">glfw</a></b> (🥈37 · ⭐ 14K) - A multi-platform library for OpenGL, OpenGL ES, Vulkan, window and input. <code><a href="https://tldrlegal.com/search?q=Zlib">❗️Zlib</a></code> - <b><a href="https://github.com/ageitgey/face_recognition">Face Recognition</a></b> (🥈36 · ⭐ 55K · 💀) - 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/open-mmlab/mmdetection">MMDetection</a></b> (🥈36 · ⭐ 31K · 💀) - 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> - <b><a href="https://github.com/facebookresearch/pytorch3d">PyTorch3D</a></b> (🥈32 · ⭐ 9.2K) - PyTorch3D is FAIRs library of reusable components for.. <code>❗Unlicensed</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> (🥈32 · ⭐ 4.6K · 💀) - 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/OlafenwaMoses/ImageAI">imageai</a></b> (🥈31 · ⭐ 8.8K · 💀) - A python library built to empower developers to build applications.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/dmlc/gluon-cv">GluonCV</a></b> (🥉29 · ⭐ 5.9K · 💀) - 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> (🥉28 · ⭐ 5.2K · 💀) - 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> (🥉27 · ⭐ 5.1K · 💀) - 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> (🥉27 · ⭐ 1.5K · 💀) - 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> (🥉25 · ⭐ 2.2K · 💤) - The friendly PIL fork. <code><a href="https://tldrlegal.com/search?q=PIL">❗️PIL</a></code> - <b><a href="https://github.com/lucidrains/deep-daze">deep-daze</a></b> (🥉23 · ⭐ 4.4K · 💀) - 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/facebookresearch/vissl">vissl</a></b> (🥉23 · ⭐ 3.3K · 💀) - 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> - <b><a href="https://github.com/tryolabs/luminoth">Luminoth</a></b> (🥉23 · ⭐ 2.4K · 💀) - 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> (🥉23 · ⭐ 1.6K · 💀) - 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/alankbi/detecto">detecto</a></b> (🥉22 · ⭐ 620 · 💀) - 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/detr">DE⫶TR</a></b> (🥉21 · ⭐ 14K · 💀) - 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> - <b><a href="https://github.com/rhsimplex/image-match">image-match</a></b> (🥉20 · ⭐ 3K · 💀) - 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> (🥉20 · ⭐ 930 · 💀) - Nudity detection with Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/imedslab/solt">solt</a></b> (🥉20 · ⭐ 260) - Streaming over lightweight data transformations. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/facebookresearch/pycls">pycls</a></b> (🥉18 · ⭐ 2.2K · 💀) - 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/jasmcaus/caer">Caer</a></b> (🥉17 · ⭐ 790 · 💀) - 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> (🥉17 · ⭐ 240 · 💀) - 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> (🥉15 · ⭐ 200 · 💀) - 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> (🥇44 · ⭐ 16K) - Network Analysis in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/networkx/networkx) (👨‍💻 770 · 🔀 3.3K · 📥 110 · 📦 390K · 📋 3.4K - 10% open · ⏱️ 21.04.2025): ``` git clone https://github.com/networkx/networkx ``` - [PyPi](https://pypi.org/project/networkx) (📥 86M / month · 📦 9.6K · ⏱️ 21.10.2024): ``` pip install networkx ``` - [Conda](https://anaconda.org/conda-forge/networkx) (📥 22M · ⏱️ 22.04.2025): ``` conda install -c conda-forge networkx ``` </details> <details><summary><b><a href="https://github.com/pyg-team/pytorch_geometric">PyTorch Geometric</a></b> (🥇40 · ⭐ 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) (👨‍💻 540 · 🔀 3.8K · 📦 8.9K · 📋 3.9K - 30% open · ⏱️ 23.04.2025): ``` git clone https://github.com/pyg-team/pytorch_geometric ``` - [PyPi](https://pypi.org/project/torch-geometric) (📥 620K / month · 📦 360 · ⏱️ 26.09.2024): ``` pip install torch-geometric ``` - [Conda](https://anaconda.org/conda-forge/pytorch_geometric) (📥 150K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pytorch_geometric ``` </details> <details><summary><b><a href="https://github.com/dmlc/dgl">dgl</a></b> (🥇36 · ⭐ 14K) - Python package built to ease deep learning on graph, on top of existing DL.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/dmlc/dgl) (👨‍💻 300 · 🔀 3K · 📦 3.9K · 📋 2.9K - 18% open · ⏱️ 11.02.2025): ``` git clone https://github.com/dmlc/dgl ``` - [PyPi](https://pypi.org/project/dgl) (📥 110K / month · 📦 150 · ⏱️ 13.05.2024): ``` pip install dgl ``` </details> <details><summary><b><a href="https://github.com/pykeen/pykeen">PyKEEN</a></b> (🥈31 · ⭐ 1.8K) - 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) (👨‍💻 43 · 🔀 200 · 📥 240 · 📦 310 · 📋 590 - 20% open · ⏱️ 24.04.2025): ``` git clone https://github.com/pykeen/pykeen ``` - [PyPi](https://pypi.org/project/pykeen) (📥 11K / month · 📦 21 · ⏱️ 24.04.2025): ``` pip install pykeen ``` </details> <details><summary><b><a href="https://github.com/graphistry/pygraphistry">pygraphistry</a></b> (🥈29 · ⭐ 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) (👨‍💻 46 · 🔀 220 · 📦 150 · 📋 360 - 53% open · ⏱️ 22.04.2025): ``` git clone https://github.com/graphistry/pygraphistry ``` - [PyPi](https://pypi.org/project/graphistry) (📥 25K / month · 📦 6 · ⏱️ 22.04.2025): ``` pip install graphistry ``` </details> <details><summary><b><a href="https://github.com/snap-stanford/ogb">ogb</a></b> (🥈29 · ⭐ 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) (👨‍💻 32 · 🔀 400 · 📦 2.5K · 📋 300 - 10% open · ⏱️ 09.12.2024): ``` git clone https://github.com/snap-stanford/ogb ``` - [PyPi](https://pypi.org/project/ogb) (📥 37K / month · 📦 22 · ⏱️ 02.11.2022): ``` pip install ogb ``` - [Conda](https://anaconda.org/conda-forge/ogb) (📥 52K · ⏱️ 22.04.2025): ``` conda install -c conda-forge ogb ``` </details> <details><summary><b><a href="https://github.com/benedekrozemberczki/pytorch_geometric_temporal">pytorch_geometric_temporal</a></b> (🥈28 · ⭐ 2.8K) - 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) (👨‍💻 37 · 🔀 390 · 📋 200 - 20% open · ⏱️ 24.03.2025): ``` git clone https://github.com/benedekrozemberczki/pytorch_geometric_temporal ``` - [PyPi](https://pypi.org/project/torch-geometric-temporal) (📥 5.6K / month · 📦 7 · ⏱️ 28.03.2025): ``` pip install torch-geometric-temporal ``` </details> <details><summary><b><a href="https://github.com/eliorc/node2vec">Node2Vec</a></b> (🥈25 · ⭐ 1.3K · 💤) - Implementation of the node2vec algorithm. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/eliorc/node2vec) (👨‍💻 16 · 🔀 250 · 📦 880 · 📋 97 - 5% open · ⏱️ 02.08.2024): ``` git clone https://github.com/eliorc/node2vec ``` - [PyPi](https://pypi.org/project/node2vec) (📥 26K / month · 📦 31 · ⏱️ 02.08.2024): ``` pip install node2vec ``` - [Conda](https://anaconda.org/conda-forge/node2vec) (📥 35K · ⏱️ 22.04.2025): ``` conda install -c conda-forge node2vec ``` </details> <details><summary><b><a href="https://github.com/rusty1s/pytorch_cluster">torch-cluster</a></b> (🥈25 · ⭐ 860) - 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) (👨‍💻 39 · 🔀 150 · 📋 180 - 17% open · ⏱️ 20.04.2025): ``` git clone https://github.com/rusty1s/pytorch_cluster ``` - [PyPi](https://pypi.org/project/torch-cluster) (📥 23K / month · 📦 62 · ⏱️ 12.10.2023): ``` pip install torch-cluster ``` - [Conda](https://anaconda.org/conda-forge/pytorch_cluster) (📥 350K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pytorch_cluster ``` </details> <details><summary><b><a href="https://github.com/DeepGraphLearning/graphvite">GraphVite</a></b> (🥉15 · ⭐ 1.2K · 💤) - GraphVite: A General and High-performance Graph Embedding.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/DeepGraphLearning/graphvite) (👨‍💻 1 · 🔀 150 · 📋 110 - 46% open · ⏱️ 14.06.2024): ``` git clone https://github.com/DeepGraphLearning/graphvite ``` - [Conda](https://anaconda.org/milagraph/graphvite) (📥 5.1K · ⏱️ 25.03.2025): ``` conda install -c milagraph graphvite ``` </details> <details><summary>Show 26 hidden projects...</summary> - <b><a href="https://github.com/igraph/python-igraph">igraph</a></b> (🥇32 · ⭐ 1.4K) - Python interface for igraph. <code><a href="http://bit.ly/2KucAZR">❗️GPL-2.0</a></code> - <b><a href="https://github.com/danielegrattarola/spektral">Spektral</a></b> (🥈28 · ⭐ 2.4K · 💀) - 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> - <b><a href="https://github.com/stellargraph/stellargraph">StellarGraph</a></b> (🥈27 · ⭐ 3K · 💀) - 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> (🥈27 · ⭐ 2.7K · 💤) - PYthon svg GrAph plotting Library. <code><a href="http://bit.ly/37RvQcA">❗️LGPL-3.0</a></code> - <b><a href="https://github.com/Accenture/AmpliGraph">AmpliGraph</a></b> (🥈26 · ⭐ 2.2K · 💀) - 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> - <b><a href="https://github.com/PaddlePaddle/PGL">Paddle Graph Learning</a></b> (🥈26 · ⭐ 1.6K · 💀) - 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> (🥉24 · ⭐ 2.2K · 💤) - Karate Club: An API Oriented Open-source Python Framework.. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/facebookresearch/PyTorch-BigGraph">PyTorch-BigGraph</a></b> (🥉23 · ⭐ 3.4K · 💀) - 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> - <b><a href="https://github.com/google-deepmind/jraph">jraph</a></b> (🥉23 · ⭐ 1.4K · 💀) - 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/graph4ai/graph4nlp">graph4nlp</a></b> (🥉22 · ⭐ 1.7K · 💀) - 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/graph_nets">graph-nets</a></b> (🥉21 · ⭐ 5.4K · 💀) - 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> (🥉21 · ⭐ 260 · 💀) - 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> (🥉20 · ⭐ 2.7K · 💀) - DeepWalk - Deep Learning for Graphs. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/divelab/DIG">DIG</a></b> (🥉20 · ⭐ 1.9K · 💀) - A library for graph deep learning research. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/snap-stanford/GraphGym">GraphGym</a></b> (🥉20 · ⭐ 1.8K · 💀) - 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/snap-stanford/deepsnap">deepsnap</a></b> (🥉20 · ⭐ 560 · 💀) - Python library assists deep learning on graphs. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/gsi-upm/sematch">Sematch</a></b> (🥉18 · ⭐ 440 · 💀) - semantic similarity framework for knowledge graph. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/deepgraph/deepgraph">DeepGraph</a></b> (🥉18 · ⭐ 290) - 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/typedb/typedb-ml">kglib</a></b> (🥉17 · ⭐ 550 · 💀) - 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/alibaba/euler">Euler</a></b> (🥉16 · ⭐ 2.9K · 💀) - 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/THUMNLab/AutoGL">AutoGL</a></b> (🥉16 · ⭐ 1.1K · 💀) - 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> - <b><a href="https://github.com/microsoft/ptgnn">ptgnn</a></b> (🥉15 · ⭐ 380 · 💀) - 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> (🥉14 · ⭐ 3.8K · 💀) - 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> (🥉14 · ⭐ 3.5K · 💀) - 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/OpenNE">OpenNE</a></b> (🥉14 · ⭐ 1.7K · 💀) - 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> - <b><a href="https://github.com/thunlp/OpenKE">OpenKE</a></b> (🥉13 · ⭐ 3.9K · 💀) - An Open-Source Package for Knowledge Embedding (KE). <code>❗Unlicensed</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> (🥇39 · ⭐ 9.7K) - 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) (👨‍💻 260 · 🔀 1.4K · 📦 3.3K · 📋 1.2K - 12% open · ⏱️ 16.04.2025): ``` git clone https://github.com/speechbrain/speechbrain ``` - [PyPi](https://pypi.org/project/speechbrain) (📥 1.3M / month · 📦 79 · ⏱️ 07.04.2025): ``` pip install speechbrain ``` </details> <details><summary><b><a href="https://github.com/espnet/espnet">espnet</a></b> (🥇38 · ⭐ 9K) - End-to-End Speech Processing Toolkit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/espnet/espnet) (👨‍💻 490 · 🔀 2.2K · 📥 84 · 📦 440 · 📋 2.5K - 14% open · ⏱️ 21.04.2025): ``` git clone https://github.com/espnet/espnet ``` - [PyPi](https://pypi.org/project/espnet) (📥 24K / month · 📦 12 · ⏱️ 04.12.2024): ``` pip install espnet ``` </details> <details><summary><b><a href="https://github.com/Uberi/speech_recognition">SpeechRecognition</a></b> (🥈35 · ⭐ 8.7K) - 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) (👨‍💻 54 · 🔀 2.4K · 📦 21 · 📋 660 - 48% open · ⏱️ 15.04.2025): ``` git clone https://github.com/Uberi/speech_recognition ``` - [PyPi](https://pypi.org/project/SpeechRecognition) (📥 1.5M / month · 📦 680 · ⏱️ 23.03.2025): ``` pip install SpeechRecognition ``` - [Conda](https://anaconda.org/conda-forge/speechrecognition) (📥 240K · ⏱️ 22.04.2025): ``` conda install -c conda-forge speechrecognition ``` </details> <details><summary><b><a href="https://github.com/librosa/librosa">librosa</a></b> (🥈35 · ⭐ 7.6K) - Python library for audio and music analysis. <code><a href="http://bit.ly/3hkKRql">ISC</a></code></summary> - [GitHub](https://github.com/librosa/librosa) (👨‍💻 120 · 🔀 980 · 📋 1.2K - 5% open · ⏱️ 11.03.2025): ``` git clone https://github.com/librosa/librosa ``` - [PyPi](https://pypi.org/project/librosa) (📥 3.6M / month · 📦 1.6K · ⏱️ 11.03.2025): ``` pip install librosa ``` - [Conda](https://anaconda.org/conda-forge/librosa) (📥 880K · ⏱️ 22.04.2025): ``` conda install -c conda-forge librosa ``` </details> <details><summary><b><a href="https://github.com/pytorch/audio">torchaudio</a></b> (🥈35 · ⭐ 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) (👨‍💻 230 · 🔀 690 · 📋 1K - 27% open · ⏱️ 18.04.2025): ``` git clone https://github.com/pytorch/audio ``` - [PyPi](https://pypi.org/project/torchaudio) (📥 13M / month · 📦 1.8K · ⏱️ 23.04.2025): ``` pip install torchaudio ``` </details> <details><summary><b><a href="https://github.com/deezer/spleeter">spleeter</a></b> (🥈33 · ⭐ 27K) - 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) (👨‍💻 22 · 🔀 2.9K · 📥 3.9M · 📦 990 · 📋 820 - 31% open · ⏱️ 02.04.2025): ``` git clone https://github.com/deezer/spleeter ``` - [PyPi](https://pypi.org/project/spleeter) (📥 30K / month · 📦 18 · ⏱️ 03.04.2025): ``` pip install spleeter ``` - [Conda](https://anaconda.org/conda-forge/spleeter) (📥 110K · ⏱️ 22.04.2025): ``` conda install -c conda-forge spleeter ``` </details> <details><summary><b><a href="https://github.com/magenta/magenta">Magenta</a></b> (🥈33 · ⭐ 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) (👨‍💻 160 · 🔀 3.7K · 📦 580 · 📋 1K - 41% open · ⏱️ 17.01.2025): ``` git clone https://github.com/magenta/magenta ``` - [PyPi](https://pypi.org/project/magenta) (📥 9.4K / month · 📦 5 · ⏱️ 01.08.2022): ``` pip install magenta ``` </details> <details><summary><b><a href="https://github.com/Picovoice/porcupine">Porcupine</a></b> (🥈31 · ⭐ 4.1K) - 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) (👨‍💻 42 · 🔀 520 · 📦 46 · 📋 570 - 0% open · ⏱️ 15.04.2025): ``` git clone https://github.com/Picovoice/Porcupine ``` - [PyPi](https://pypi.org/project/pvporcupine) (📥 20K / month · 📦 38 · ⏱️ 05.02.2025): ``` pip install pvporcupine ``` </details> <details><summary><b><a href="https://github.com/iver56/audiomentations">audiomentations</a></b> (🥈31 · ⭐ 2K) - A Python library for audio data augmentation. Useful for making.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/iver56/audiomentations) (👨‍💻 32 · 🔀 200 · 📦 750 · 📋 200 - 26% open · ⏱️ 24.04.2025): ``` git clone https://github.com/iver56/audiomentations ``` - [PyPi](https://pypi.org/project/audiomentations) (📥 73K / month · 📦 25 · ⏱️ 20.03.2025): ``` pip install audiomentations ``` </details> <details><summary><b><a href="https://github.com/bastibe/python-soundfile">python-soundfile</a></b> (🥉29 · ⭐ 760) - 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) (👨‍💻 37 · 🔀 110 · 📥 21K · 📦 61K · 📋 260 - 46% open · ⏱️ 25.01.2025): ``` git clone https://github.com/bastibe/python-soundfile ``` - [PyPi](https://pypi.org/project/soundfile) (📥 5.6M / month · 📦 1.1K · ⏱️ 25.01.2025): ``` 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> (🥉29 · ⭐ 750) - Python library for reading audio file metadata. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/tinytag/tinytag) (👨‍💻 27 · 🔀 100 · 📦 1.2K · 📋 120 - 3% open · ⏱️ 23.04.2025): ``` git clone https://github.com/devsnd/tinytag ``` - [PyPi](https://pypi.org/project/tinytag) (📥 61K / month · 📦 120 · ⏱️ 23.04.2025): ``` pip install tinytag ``` </details> <details><summary><b><a href="https://github.com/tyiannak/pyAudioAnalysis">pyAudioAnalysis</a></b> (🥉28 · ⭐ 6K) - Python Audio Analysis Library: Feature Extraction,.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/tyiannak/pyAudioAnalysis) (👨‍💻 28 · 🔀 1.2K · 📦 610 · 📋 320 - 62% open · ⏱️ 28.03.2025): ``` git clone https://github.com/tyiannak/pyAudioAnalysis ``` - [PyPi](https://pypi.org/project/pyAudioAnalysis) (📥 17K / month · 📦 12 · ⏱️ 07.02.2022): ``` pip install pyAudioAnalysis ``` </details> <details><summary><b><a href="https://github.com/CPJKU/madmom">Madmom</a></b> (🥉27 · ⭐ 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) (👨‍💻 24 · 🔀 220 · 📦 490 · 📋 280 - 24% open · ⏱️ 25.08.2024): ``` git clone https://github.com/CPJKU/madmom ``` - [PyPi](https://pypi.org/project/madmom) (📥 3.4K / month · 📦 27 · ⏱️ 14.11.2018): ``` pip install madmom ``` </details> <details><summary><b><a href="https://github.com/magenta/ddsp">DDSP</a></b> (🥉25 · ⭐ 3K · 💤) - 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) (👨‍💻 32 · 🔀 340 · 📦 64 · 📋 170 - 28% open · ⏱️ 23.09.2024): ``` git clone https://github.com/magenta/ddsp ``` - [PyPi](https://pypi.org/project/ddsp) (📥 5.3K / month · 📦 1 · ⏱️ 25.05.2022): ``` pip install ddsp ``` - [Conda](https://anaconda.org/conda-forge/ddsp) (📥 22K · ⏱️ 22.04.2025): ``` conda install -c conda-forge ddsp ``` </details> <details><summary><b><a href="https://github.com/mozilla/DeepSpeech">DeepSpeech</a></b> (🥉23 · ⭐ 26K) - DeepSpeech is an open source embedded (offline, on-device).. <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></summary> - [GitHub](https://github.com/mozilla/DeepSpeech) (👨‍💻 140 · 🔀 4K): ``` git clone https://github.com/mozilla/DeepSpeech ``` - [PyPi](https://pypi.org/project/deepspeech) (📥 18K / month · 📦 24 · ⏱️ 19.12.2020): ``` pip install deepspeech ``` - [Conda](https://anaconda.org/conda-forge/deepspeech) (📥 3.8K · ⏱️ 22.04.2025): ``` conda install -c conda-forge deepspeech ``` </details> <details><summary><b><a href="https://github.com/adefossez/julius">Julius</a></b> (🥉23 · ⭐ 440) - 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></summary> - [GitHub](https://github.com/adefossez/julius) (👨‍💻 3 · 🔀 25 · 📦 2.8K · 📋 12 - 16% open · ⏱️ 17.02.2025): ``` git clone https://github.com/adefossez/julius ``` - [PyPi](https://pypi.org/project/julius) (📥 410K / month · 📦 44 · ⏱️ 20.09.2022): ``` pip install julius ``` </details> <details><summary>Show 13 hidden projects...</summary> - <b><a href="https://github.com/coqui-ai/TTS">Coqui TTS</a></b> (🥇36 · ⭐ 40K · 💀) - - 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> - <b><a href="https://github.com/jiaaro/pydub">Pydub</a></b> (🥇36 · ⭐ 9.3K · 💀) - 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/beetbox/audioread">audioread</a></b> (🥈30 · ⭐ 510 · 💀) - cross-library (GStreamer + Core Audio + MAD + FFmpeg) audio.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/MTG/essentia">Essentia</a></b> (🥉29 · ⭐ 3K) - C++ library for audio and music analysis, description and.. <code><a href="http://bit.ly/3pwmjO5">❗️AGPL-3.0</a></code> - <b><a href="https://github.com/aubio/aubio">aubio</a></b> (🥉28 · ⭐ 3.4K · 💀) - a library for audio and music analysis. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/mozilla/TTS">TTS</a></b> (🥉26 · ⭐ 9.8K · 💀) - 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> (🥉25 · ⭐ 2.4K · 💀) - 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> (🥉23 · ⭐ 6.5K · 💀) - Audio fingerprinting and recognition in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/KinWaiCheuk/nnAudio">nnAudio</a></b> (🥉23 · ⭐ 1.1K · 💀) - Audio processing by using pytorch 1D convolution network. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/keunwoochoi/kapre">kapre</a></b> (🥉22 · ⭐ 930 · 💀) - 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> (🥉21 · ⭐ 380) - scalable audio processing framework and server written in Python. <code><a href="http://bit.ly/3pwmjO5">❗️AGPL-3.0</a></code> - <b><a href="https://github.com/bmcfee/muda">Muda</a></b> (🥉18 · ⭐ 230 · 💀) - 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> (🥉10 · ⭐ 540 · 💀) - 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> (🥇43 · ⭐ 13K) - 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) (👨‍💻 290 · 🔀 2.1K · 📦 9K · 📋 3.2K - 13% open · ⏱️ 23.04.2025): ``` git clone https://github.com/visgl/deck.gl ``` - [PyPi](https://pypi.org/project/pydeck) (📥 8.5M / month · 📦 160 · ⏱️ 21.03.2025): ``` pip install pydeck ``` - [Conda](https://anaconda.org/conda-forge/pydeck) (📥 740K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pydeck ``` - [npm](https://www.npmjs.com/package/deck.gl) (📥 610K / month · 📦 340 · ⏱️ 18.04.2025): ``` npm install deck.gl ``` </details> <details><summary><b><a href="https://github.com/shapely/shapely">Shapely</a></b> (🥇41 · ⭐ 4.1K) - Manipulation and analysis of geometric objects. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/shapely/shapely) (👨‍💻 170 · 🔀 580 · 📥 3.8K · 📦 100K · 📋 1.3K - 19% open · ⏱️ 03.04.2025): ``` git clone https://github.com/shapely/shapely ``` - [PyPi](https://pypi.org/project/shapely) (📥 45M / month · 📦 3.9K · ⏱️ 03.04.2025): ``` pip install shapely ``` - [Conda](https://anaconda.org/conda-forge/shapely) (📥 12M · ⏱️ 22.04.2025): ``` conda install -c conda-forge shapely ``` </details> <details><summary><b><a href="https://github.com/python-visualization/folium">folium</a></b> (🥇39 · ⭐ 7.1K) - Python Data. Leaflet.js Maps. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/python-visualization/folium) (👨‍💻 170 · 🔀 2.2K · 📦 58K · 📋 1.2K - 8% open · ⏱️ 22.04.2025): ``` git clone https://github.com/python-visualization/folium ``` - [PyPi](https://pypi.org/project/folium) (📥 2.2M / month · 📦 860 · ⏱️ 27.02.2025): ``` pip install folium ``` - [Conda](https://anaconda.org/conda-forge/folium) (📥 3.7M · ⏱️ 22.04.2025): ``` conda install -c conda-forge folium ``` </details> <details><summary><b><a href="https://github.com/geopandas/geopandas">GeoPandas</a></b> (🥈38 · ⭐ 4.7K) - 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) (👨‍💻 240 · 🔀 950 · 📥 3K · 📦 54K · 📋 1.7K - 25% open · ⏱️ 17.04.2025): ``` git clone https://github.com/geopandas/geopandas ``` - [PyPi](https://pypi.org/project/geopandas) (📥 7.6M / month · 📦 2.8K · ⏱️ 02.07.2024): ``` pip install geopandas ``` - [Conda](https://anaconda.org/conda-forge/geopandas) (📥 4.6M · ⏱️ 22.04.2025): ``` conda install -c conda-forge geopandas ``` </details> <details><summary><b><a href="https://github.com/rasterio/rasterio">Rasterio</a></b> (🥈37 · ⭐ 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) (👨‍💻 170 · 🔀 540 · 📥 1K · 📦 17K · 📋 1.9K - 8% open · ⏱️ 14.04.2025): ``` git clone https://github.com/rasterio/rasterio ``` - [PyPi](https://pypi.org/project/rasterio) (📥 2.3M / month · 📦 1.5K · ⏱️ 02.12.2024): ``` pip install rasterio ``` - [Conda](https://anaconda.org/conda-forge/rasterio) (📥 4.6M · ⏱️ 22.04.2025): ``` conda install -c conda-forge rasterio ``` </details> <details><summary><b><a href="https://github.com/pyproj4/pyproj">pyproj</a></b> (🥈37 · ⭐ 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) (👨‍💻 69 · 🔀 220 · 📦 43K · 📋 630 - 5% open · ⏱️ 01.04.2025): ``` git clone https://github.com/pyproj4/pyproj ``` - [PyPi](https://pypi.org/project/pyproj) (📥 11M / month · 📦 1.9K · ⏱️ 16.02.2025): ``` pip install pyproj ``` - [Conda](https://anaconda.org/conda-forge/pyproj) (📥 10M · ⏱️ 22.04.2025): ``` conda install -c conda-forge pyproj ``` </details> <details><summary><b><a href="https://github.com/Esri/arcgis-python-api">ArcGIS API</a></b> (🥈36 · ⭐ 2K) - 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) (👨‍💻 97 · 🔀 1.1K · 📥 15K · 📦 940 · 📋 840 - 8% open · ⏱️ 21.04.2025): ``` git clone https://github.com/Esri/arcgis-python-api ``` - [PyPi](https://pypi.org/project/arcgis) (📥 97K / month · 📦 41 · ⏱️ 17.04.2025): ``` 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> (🥈34 · ⭐ 1.2K) - 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) (👨‍💻 78 · 🔀 210 · 📦 25K · 📋 810 - 4% open · ⏱️ 20.02.2025): ``` git clone https://github.com/Toblerity/Fiona ``` - [PyPi](https://pypi.org/project/fiona) (📥 4.3M / month · 📦 380 · ⏱️ 16.09.2024): ``` pip install fiona ``` - [Conda](https://anaconda.org/conda-forge/fiona) (📥 6.8M · ⏱️ 22.04.2025): ``` conda install -c conda-forge fiona ``` </details> <details><summary><b><a href="https://github.com/jupyter-widgets/ipyleaflet">ipyleaflet</a></b> (🥉32 · ⭐ 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) (👨‍💻 92 · 🔀 360 · 📦 16K · 📋 660 - 45% open · ⏱️ 05.12.2024): ``` git clone https://github.com/jupyter-widgets/ipyleaflet ``` - [PyPi](https://pypi.org/project/ipyleaflet) (📥 210K / month · 📦 280 · ⏱️ 22.07.2024): ``` pip install ipyleaflet ``` - [Conda](https://anaconda.org/conda-forge/ipyleaflet) (📥 1.4M · ⏱️ 22.04.2025): ``` conda install -c conda-forge ipyleaflet ``` - [npm](https://www.npmjs.com/package/jupyter-leaflet) (📥 3.7K / month · 📦 9 · ⏱️ 22.07.2024): ``` npm install jupyter-leaflet ``` </details> <details><summary><b><a href="https://github.com/pysal/pysal">PySAL</a></b> (🥉31 · ⭐ 1.4K) - 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) (👨‍💻 79 · 🔀 300 · 📦 1.8K · 📋 660 - 3% open · ⏱️ 06.02.2025): ``` git clone https://github.com/pysal/pysal ``` - [PyPi](https://pypi.org/project/pysal) (📥 28K / month · 📦 59 · ⏱️ 06.02.2025): ``` pip install pysal ``` - [Conda](https://anaconda.org/conda-forge/pysal) (📥 620K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pysal ``` </details> <details><summary><b><a href="https://github.com/jazzband/geojson">geojson</a></b> (🥉31 · ⭐ 960) - Python bindings and utilities for GeoJSON. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/jazzband/geojson) (👨‍💻 58 · 🔀 120 · 📦 20K · 📋 100 - 25% open · ⏱️ 21.12.2024): ``` git clone https://github.com/jazzband/geojson ``` - [PyPi](https://pypi.org/project/geojson) (📥 3M / month · 📦 720 · ⏱️ 21.12.2024): ``` pip install geojson ``` - [Conda](https://anaconda.org/conda-forge/geojson) (📥 950K · ⏱️ 22.04.2025): ``` conda install -c conda-forge geojson ``` </details> <details><summary><b><a href="https://github.com/holoviz/geoviews">GeoViews</a></b> (🥉28 · ⭐ 610) - Simple, concise geographical visualization in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/holoviz/geoviews) (👨‍💻 33 · 🔀 77 · 📦 1.3K · 📋 350 - 31% open · ⏱️ 08.04.2025): ``` git clone https://github.com/holoviz/geoviews ``` - [PyPi](https://pypi.org/project/geoviews) (📥 18K / month · 📦 63 · ⏱️ 17.12.2024): ``` pip install geoviews ``` - [Conda](https://anaconda.org/conda-forge/geoviews) (📥 290K · ⏱️ 22.04.2025): ``` conda install -c conda-forge geoviews ``` </details> <details><summary><b><a href="https://github.com/mapbox/mapboxgl-jupyter">Mapbox GL</a></b> (🥉24 · ⭐ 680) - 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></summary> - [GitHub](https://github.com/mapbox/mapboxgl-jupyter) (👨‍💻 23 · 🔀 140 · 📦 240 · 📋 110 - 38% open · ⏱️ 06.02.2025): ``` git clone https://github.com/mapbox/mapboxgl-jupyter ``` - [PyPi](https://pypi.org/project/mapboxgl) (📥 8.5K / month · 📦 12 · ⏱️ 02.06.2019): ``` pip install mapboxgl ``` </details> <details><summary><b><a href="https://github.com/geospace-code/pymap3d">pymap3d</a></b> (🥉24 · ⭐ 410) - pure-Python (Numpy optional) 3D coordinate conversions for geospace ecef.. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary> - [GitHub](https://github.com/geospace-code/pymap3d) (👨‍💻 19 · 🔀 87 · 📦 500 · 📋 60 - 15% open · ⏱️ 08.01.2025): ``` git clone https://github.com/geospace-code/pymap3d ``` - [PyPi](https://pypi.org/project/pymap3d) (📥 310K / month · 📦 44 · ⏱️ 11.02.2024): ``` pip install pymap3d ``` - [Conda](https://anaconda.org/conda-forge/pymap3d) (📥 100K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pymap3d ``` </details> <details><summary>Show 8 hidden projects...</summary> - <b><a href="https://github.com/pytroll/satpy">Satpy</a></b> (🥈34 · ⭐ 1.1K) - Python package for earth-observing satellite data processing. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/geopy/geopy">geopy</a></b> (🥉33 · ⭐ 4.6K · 💀) - 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> (🥉33 · ⭐ 1.6K · 💀) - Python Geocoder. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/sentinelsat/sentinelsat">Sentinelsat</a></b> (🥉27 · ⭐ 1K · 💀) - Search and download Copernicus Sentinel satellite images. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/earthlab/earthpy">EarthPy</a></b> (🥉27 · ⭐ 520 · 💀) - 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> (🥉26 · ⭐ 12K) - Draw pretty maps from OpenStreetMap data! Built with osmnx.. <code><a href="http://bit.ly/3pwmjO5">❗️AGPL-3.0</a></code> - <b><a href="https://github.com/pbugnion/gmaps">gmaps</a></b> (🥉23 · ⭐ 760 · 💀) - 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> (🥉22 · ⭐ 1K · 💀) - 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> (🥇41 · ⭐ 17K) - 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) (👨‍💻 130 · 🔀 2.6K · 📦 73K · 📋 1.6K - 11% open · ⏱️ 23.04.2025): ``` git clone https://github.com/ranaroussi/yfinance ``` - [PyPi](https://pypi.org/project/yfinance) (📥 3.1M / month · 📦 940 · ⏱️ 23.04.2025): ``` pip install yfinance ``` - [Conda](https://anaconda.org/ranaroussi/yfinance) (📥 98K · ⏱️ 25.03.2025): ``` conda install -c ranaroussi yfinance ``` </details> <details><summary><b><a href="https://github.com/microsoft/qlib">Qlib</a></b> (🥈31 · ⭐ 19K) - 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) (👨‍💻 140 · 🔀 3K · 📥 790 · 📦 21 · 📋 960 - 25% open · ⏱️ 02.04.2025): ``` git clone https://github.com/microsoft/qlib ``` - [PyPi](https://pypi.org/project/pyqlib) (📥 8.4K / month · 📦 1 · ⏱️ 23.12.2024): ``` pip install pyqlib ``` </details> <details><summary><b><a href="https://github.com/pmorissette/bt">bt</a></b> (🥈31 · ⭐ 2.5K) - bt - flexible backtesting for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/pmorissette/bt) (👨‍💻 34 · 🔀 440 · 📦 1.7K · 📋 350 - 23% open · ⏱️ 08.04.2025): ``` git clone https://github.com/pmorissette/bt ``` - [PyPi](https://pypi.org/project/bt) (📥 11K / month · 📦 15 · ⏱️ 12.04.2025): ``` pip install bt ``` - [Conda](https://anaconda.org/conda-forge/bt) (📥 80K · ⏱️ 22.04.2025): ``` conda install -c conda-forge bt ``` </details> <details><summary><b><a href="https://github.com/pmorissette/ffn">ffn</a></b> (🥈29 · ⭐ 2.2K) - ffn - a financial function library for Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/pmorissette/ffn) (👨‍💻 36 · 🔀 310 · 📦 550 · 📋 130 - 16% open · ⏱️ 01.04.2025): ``` git clone https://github.com/pmorissette/ffn ``` - [PyPi](https://pypi.org/project/ffn) (📥 22K / month · 📦 22 · ⏱️ 11.02.2025): ``` pip install ffn ``` - [Conda](https://anaconda.org/conda-forge/ffn) (📥 18K · ⏱️ 22.04.2025): ``` conda install -c conda-forge ffn ``` </details> <details><summary><b><a href="https://github.com/tensortrade-org/tensortrade">TensorTrade</a></b> (🥉27 · ⭐ 5K · 💤) - 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) (👨‍💻 61 · 🔀 1K · 📦 69 · 📋 260 - 20% open · ⏱️ 09.06.2024): ``` git clone https://github.com/tensortrade-org/tensortrade ``` - [PyPi](https://pypi.org/project/tensortrade) (📥 1.9K / month · 📦 1 · ⏱️ 10.05.2021): ``` pip install tensortrade ``` - [Conda](https://anaconda.org/conda-forge/tensortrade) (📥 4.8K · ⏱️ 22.04.2025): ``` conda install -c conda-forge tensortrade ``` </details> <details><summary><b><a href="https://github.com/RomelTorres/alpha_vantage">Alpha Vantage</a></b> (🥉27 · ⭐ 4.5K · 💤) - 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) (👨‍💻 44 · 🔀 750 · 📋 290 - 0% open · ⏱️ 18.07.2024): ``` git clone https://github.com/RomelTorres/alpha_vantage ``` - [PyPi](https://pypi.org/project/alpha_vantage) (📥 59K / month · 📦 35 · ⏱️ 18.07.2024): ``` pip install alpha_vantage ``` - [Conda](https://anaconda.org/conda-forge/alpha_vantage) (📥 8.9K · ⏱️ 22.04.2025): ``` conda install -c conda-forge alpha_vantage ``` </details> <details><summary><b><a href="https://github.com/jealous/stockstats">stockstats</a></b> (🥉26 · ⭐ 1.4K) - 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) (👨‍💻 10 · 🔀 300 · 📦 1.2K · 📋 130 - 11% open · ⏱️ 02.02.2025): ``` git clone https://github.com/jealous/stockstats ``` - [PyPi](https://pypi.org/project/stockstats) (📥 13K / month · 📦 12 · ⏱️ 02.02.2025): ``` pip install stockstats ``` </details> <details><summary><b><a href="https://github.com/cuemacro/finmarketpy">finmarketpy</a></b> (🥉25 · ⭐ 3.6K) - 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) (👨‍💻 19 · 🔀 510 · 📥 57 · 📦 16 · 📋 35 - 88% open · ⏱️ 10.03.2025): ``` git clone https://github.com/cuemacro/finmarketpy ``` - [PyPi](https://pypi.org/project/finmarketpy) (📥 510 / month · ⏱️ 10.03.2025): ``` pip install finmarketpy ``` </details> <details><summary><b><a href="https://github.com/google/tf-quant-finance">tf-quant-finance</a></b> (🥉22 · ⭐ 4.8K) - 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) (👨‍💻 48 · 🔀 600 · 📋 63 - 55% open · ⏱️ 21.03.2025): ``` git clone https://github.com/google/tf-quant-finance ``` - [PyPi](https://pypi.org/project/tf-quant-finance) (📥 500 / month · 📦 3 · ⏱️ 19.08.2022): ``` pip install tf-quant-finance ``` </details> <details><summary>Show 16 hidden projects...</summary> - <b><a href="https://github.com/quantopian/zipline">zipline</a></b> (🥇33 · ⭐ 18K · 💀) - Zipline, a Pythonic Algorithmic Trading Library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/quantopian/pyfolio">pyfolio</a></b> (🥇32 · ⭐ 5.9K · 💀) - Portfolio and risk analytics in Python. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/bashtage/arch">arch</a></b> (🥇32 · ⭐ 1.4K) - ARCH models in Python. <code>❗Unlicensed</code> - <b><a href="https://github.com/bukosabino/ta">ta</a></b> (🥈31 · ⭐ 4.6K · 💀) - 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> (🥈29 · ⭐ 17K · 💀) - Python Backtesting library for trading strategies. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/kernc/backtesting.py">Backtesting.py</a></b> (🥈28 · ⭐ 6.4K) - Backtest trading strategies in Python. <code><a href="http://bit.ly/3pwmjO5">❗️AGPL-3.0</a></code> - <b><a href="https://github.com/quantopian/alphalens">Alphalens</a></b> (🥈28 · ⭐ 3.7K · 💀) - Performance analysis of predictive (alpha) stock factors. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/erdewit/ib_insync">IB-insync</a></b> (🥈28 · ⭐ 3K · 💀) - Python sync/async framework for Interactive Brokers API. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code> - <b><a href="https://github.com/quantopian/empyrical">empyrical</a></b> (🥈28 · ⭐ 1.4K · 💀) - 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> (🥉26 · ⭐ 2.5K · 💀) - 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> (🥉24 · ⭐ 2.2K · 💀) - Common financial technical indicators implemented in Pandas. <code><a href="http://bit.ly/37RvQcA">❗️LGPL-3.0</a></code> - <b><a href="https://github.com/CryptoSignal/Crypto-Signal">Crypto Signals</a></b> (🥉22 · ⭐ 5.2K · 💀) - 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> (🥉22 · ⭐ 1.5K · 💀) - A program for financial portfolio management, analysis and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/gbeced/pyalgotrade">PyAlgoTrade</a></b> (🥉20 · ⭐ 4.5K · 💀) - Python Algorithmic Trading Library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/tradytics/surpriver">surpriver</a></b> (🥉12 · ⭐ 1.8K · 💀) - Find big moving stocks before they move using machine.. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/alvarobartt/pyrtfolio">pyrtfolio</a></b> (🥉10 · ⭐ 150 · 💀) - Python package to generate stock portfolios. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-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> (🥇41 · ⭐ 8.4K) - 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) (👨‍💻 460 · 🔀 1.5K · 📥 110 · 📦 4.3K · 📋 2.9K - 38% open · ⏱️ 23.04.2025): ``` git clone https://github.com/alan-turing-institute/sktime ``` - [PyPi](https://pypi.org/project/sktime) (📥 1M / month · 📦 140 · ⏱️ 12.04.2025): ``` pip install sktime ``` - [Conda](https://anaconda.org/conda-forge/sktime-all-extras) (📥 1.1M · ⏱️ 22.04.2025): ``` conda install -c conda-forge sktime-all-extras ``` </details> <details><summary><b><a href="https://github.com/Nixtla/statsforecast">StatsForecast</a></b> (🥇34 · ⭐ 4.2K) - 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) (👨‍💻 51 · 🔀 300 · 📦 1.6K · 📋 360 - 29% open · ⏱️ 23.04.2025): ``` git clone https://github.com/Nixtla/statsforecast ``` - [PyPi](https://pypi.org/project/statsforecast) (📥 980K / month · 📦 68 · ⏱️ 18.02.2025): ``` pip install statsforecast ``` - [Conda](https://anaconda.org/conda-forge/statsforecast) (📥 170K · ⏱️ 22.04.2025): ``` conda install -c conda-forge statsforecast ``` </details> <details><summary><b><a href="https://github.com/facebook/prophet">Prophet</a></b> (🥇33 · ⭐ 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) (👨‍💻 180 · 🔀 4.5K · 📥 3K · 📦 21 · 📋 2.2K - 20% open · ⏱️ 20.10.2024): ``` git clone https://github.com/facebook/prophet ``` - [PyPi](https://pypi.org/project/fbprophet) (📥 240K / month · 📦 91 · ⏱️ 05.09.2020): ``` pip install fbprophet ``` - [Conda](https://anaconda.org/conda-forge/prophet) (📥 1.4M · ⏱️ 22.04.2025): ``` conda install -c conda-forge prophet ``` </details> <details><summary><b><a href="https://github.com/unit8co/darts">Darts</a></b> (🥇33 · ⭐ 8.5K) - 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) (👨‍💻 130 · 🔀 920 · 📋 1.7K - 14% open · ⏱️ 20.04.2025): ``` git clone https://github.com/unit8co/darts ``` - [PyPi](https://pypi.org/project/u8darts) (📥 78K / month · 📦 10 · ⏱️ 18.04.2025): ``` pip install u8darts ``` - [Conda](https://anaconda.org/conda-forge/u8darts-all) (📥 76K · ⏱️ 22.04.2025): ``` conda install -c conda-forge u8darts-all ``` - [Docker Hub](https://hub.docker.com/r/unit8/darts) (📥 1.4K · ⏱️ 18.04.2025): ``` docker pull unit8/darts ``` </details> <details><summary><b><a href="https://github.com/blue-yonder/tsfresh">tsfresh</a></b> (🥈32 · ⭐ 8.7K) - 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) (👨‍💻 99 · 🔀 1.2K · 📦 21 · 📋 550 - 12% open · ⏱️ 16.02.2025): ``` git clone https://github.com/blue-yonder/tsfresh ``` - [PyPi](https://pypi.org/project/tsfresh) (📥 250K / month · 📦 100 · ⏱️ 16.02.2025): ``` pip install tsfresh ``` - [Conda](https://anaconda.org/conda-forge/tsfresh) (📥 1.4M · ⏱️ 22.04.2025): ``` conda install -c conda-forge tsfresh ``` </details> <details><summary><b><a href="https://github.com/sktime/pytorch-forecasting">pytorch-forecasting</a></b> (🥈32 · ⭐ 4.3K) - Time series forecasting with PyTorch. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/sktime/pytorch-forecasting) (👨‍💻 67 · 🔀 660 · 📦 570 · 📋 840 - 60% open · ⏱️ 18.04.2025): ``` git clone https://github.com/jdb78/pytorch-forecasting ``` - [PyPi](https://pypi.org/project/pytorch-forecasting) (📥 140K / month · 📦 22 · ⏱️ 06.02.2025): ``` pip install pytorch-forecasting ``` - [Conda](https://anaconda.org/conda-forge/pytorch-forecasting) (📥 76K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pytorch-forecasting ``` </details> <details><summary><b><a href="https://github.com/TDAmeritrade/stumpy">STUMPY</a></b> (🥈32 · ⭐ 3.9K) - 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) (👨‍💻 41 · 🔀 330 · 📦 1.2K · 📋 530 - 13% open · ⏱️ 08.04.2025): ``` git clone https://github.com/TDAmeritrade/stumpy ``` - [PyPi](https://pypi.org/project/stumpy) (📥 300K / month · 📦 30 · ⏱️ 09.07.2024): ``` pip install stumpy ``` - [Conda](https://anaconda.org/conda-forge/stumpy) (📥 1.1M · ⏱️ 22.04.2025): ``` conda install -c conda-forge stumpy ``` </details> <details><summary><b><a href="https://github.com/Nixtla/neuralforecast">NeuralForecast</a></b> (🥈32 · ⭐ 3.5K) - 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) (👨‍💻 50 · 🔀 400 · 📦 350 · 📋 610 - 17% open · ⏱️ 10.04.2025): ``` git clone https://github.com/Nixtla/neuralforecast ``` - [PyPi](https://pypi.org/project/neuralforecast) (📥 70K / month · 📦 26 · ⏱️ 28.02.2025): ``` pip install neuralforecast ``` - [Conda](https://anaconda.org/conda-forge/neuralforecast) (📥 36K · ⏱️ 22.04.2025): ``` conda install -c conda-forge neuralforecast ``` </details> <details><summary><b><a href="https://github.com/alkaline-ml/pmdarima">pmdarima</a></b> (🥈32 · ⭐ 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) (👨‍💻 23 · 🔀 240 · 📦 12K · 📋 340 - 19% open · ⏱️ 07.11.2024): ``` git clone https://github.com/alkaline-ml/pmdarima ``` - [PyPi](https://pypi.org/project/pmdarima) (📥 2.7M / month · 📦 150 · ⏱️ 23.10.2023): ``` pip install pmdarima ``` - [Conda](https://anaconda.org/conda-forge/pmdarima) (📥 1.3M · ⏱️ 22.04.2025): ``` conda install -c conda-forge pmdarima ``` </details> <details><summary><b><a href="https://github.com/tslearn-team/tslearn">tslearn</a></b> (🥈31 · ⭐ 3K · 💤) - 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) (👨‍💻 43 · 🔀 340 · 📦 1.7K · 📋 340 - 41% open · ⏱️ 01.07.2024): ``` git clone https://github.com/tslearn-team/tslearn ``` - [PyPi](https://pypi.org/project/tslearn) (📥 390K / month · 📦 79 · ⏱️ 12.12.2023): ``` pip install tslearn ``` - [Conda](https://anaconda.org/conda-forge/tslearn) (📥 1.6M · ⏱️ 22.04.2025): ``` conda install -c conda-forge tslearn ``` </details> <details><summary><b><a href="https://github.com/skforecast/skforecast">skforecast</a></b> (🥈31 · ⭐ 1.3K) - 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) (👨‍💻 19 · 🔀 160 · 📦 440 · 📋 190 - 13% open · ⏱️ 01.04.2025): ``` git clone https://github.com/JoaquinAmatRodrigo/skforecast ``` - [PyPi](https://pypi.org/project/skforecast) (📥 88K / month · 📦 18 · ⏱️ 18.03.2025): ``` pip install skforecast ``` </details> <details><summary><b><a href="https://github.com/awslabs/gluonts">GluonTS</a></b> (🥈30 · ⭐ 4.9K) - 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) (👨‍💻 120 · 🔀 780 · 📋 970 - 34% open · ⏱️ 08.04.2025): ``` git clone https://github.com/awslabs/gluon-ts ``` - [PyPi](https://pypi.org/project/gluonts) (📥 910K / month · 📦 36 · ⏱️ 08.04.2025): ``` pip install gluonts ``` - [Conda](https://anaconda.org/anaconda/gluonts) (📥 1.8K · ⏱️ 22.04.2025): ``` conda install -c anaconda gluonts ``` </details> <details><summary><b><a href="https://github.com/python-streamz/streamz">Streamz</a></b> (🥉28 · ⭐ 1.3K) - 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) (👨‍💻 49 · 🔀 150 · 📦 540 · 📋 270 - 44% open · ⏱️ 22.11.2024): ``` git clone https://github.com/python-streamz/streamz ``` - [PyPi](https://pypi.org/project/streamz) (📥 21K / month · 📦 57 · ⏱️ 27.07.2022): ``` pip install streamz ``` - [Conda](https://anaconda.org/conda-forge/streamz) (📥 2M · ⏱️ 22.04.2025): ``` conda install -c conda-forge streamz ``` </details> <details><summary><b><a href="https://github.com/ourownstory/neural_prophet">NeuralProphet</a></b> (🥉26 · ⭐ 4.1K · 💤) - 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) (👨‍💻 56 · 🔀 490 · 📋 560 - 11% open · ⏱️ 13.09.2024): ``` git clone https://github.com/ourownstory/neural_prophet ``` - [PyPi](https://pypi.org/project/neuralprophet) (📥 82K / month · 📦 8 · ⏱️ 26.06.2024): ``` pip install neuralprophet ``` </details> <details><summary><b><a href="https://github.com/linkedin/greykite">greykite</a></b> (🥉23 · ⭐ 1.8K · 📈) - 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) (👨‍💻 10 · 🔀 110 · 📥 36 · 📦 43 · 📋 110 - 10% open · ⏱️ 20.02.2025): ``` git clone https://github.com/linkedin/greykite ``` - [PyPi](https://pypi.org/project/greykite) (📥 9.5K / month · ⏱️ 20.02.2025): ``` pip install greykite ``` </details> <details><summary><b><a href="https://github.com/fraunhoferportugal/tsfel">TSFEL</a></b> (🥉22 · ⭐ 1K) - 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) (👨‍💻 20 · 🔀 140 · 📦 200 · 📋 82 - 12% open · ⏱️ 17.10.2024): ``` git clone https://github.com/fraunhoferportugal/tsfel ``` - [PyPi](https://pypi.org/project/tsfel) (📥 8.7K / month · 📦 7 · ⏱️ 12.09.2024): ``` pip install tsfel ``` </details> <details><summary><b><a href="https://github.com/wwrechard/pydlm">pydlm</a></b> (🥉20 · ⭐ 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) (👨‍💻 7 · 🔀 98 · 📦 39 · 📋 51 - 70% open · ⏱️ 07.09.2024): ``` git clone https://github.com/wwrechard/pydlm ``` - [PyPi](https://pypi.org/project/pydlm) (📥 67K / month · 📦 2 · ⏱️ 13.08.2024): ``` pip install pydlm ``` </details> <details><summary><b><a href="https://github.com/predict-idlab/tsflex">tsflex</a></b> (🥉20 · ⭐ 420 · 💤) - Flexible time series feature extraction & processing. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/predict-idlab/tsflex) (👨‍💻 6 · 🔀 26 · 📦 22 · 📋 56 - 58% open · ⏱️ 06.09.2024): ``` git clone https://github.com/predict-idlab/tsflex ``` - [PyPi](https://pypi.org/project/tsflex) (📥 2.2K / month · 📦 2 · ⏱️ 06.09.2024): ``` pip install tsflex ``` - [Conda](https://anaconda.org/conda-forge/tsflex) (📥 32K · ⏱️ 22.04.2025): ``` conda install -c conda-forge tsflex ``` </details> <details><summary><b><a href="https://github.com/AutoViML/Auto_TS">Auto TS</a></b> (🥉18 · ⭐ 750 · 💤) - 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) (👨‍💻 13 · 🔀 120 · 📋 90 - 2% open · ⏱️ 05.05.2024): ``` git clone https://github.com/AutoViML/Auto_TS ``` - [PyPi](https://pypi.org/project/auto-ts) (📥 3.2K / month · ⏱️ 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> (🥉28 · ⭐ 1.8K · 💀) - 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> (🥉25 · ⭐ 2.1K · 💀) - Open source time series library for Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> - <b><a href="https://github.com/arundo/adtk">ADTK</a></b> (🥉23 · ⭐ 1.2K · 💀) - 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/linkedin/luminol">luminol</a></b> (🥉22 · ⭐ 1.2K · 💀) - Anomaly Detection and Correlation library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/dmbee/seglearn">seglearn</a></b> (🥉21 · ⭐ 570 · 💀) - Python module for machine learning time series:. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> - <b><a href="https://github.com/X-DataInitiative/tick">tick</a></b> (🥉21 · ⭐ 500 · 💀) - 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/target/matrixprofile-ts">matrixprofile-ts</a></b> (🥉19 · ⭐ 740 · 💀) - 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> (🥉14 · ⭐ 520 · 💀) - 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> (🥉14 · ⭐ 350 · 💀) - 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> (🥉8 · ⭐ 69 · 💀) - 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> (🥇39 · ⭐ 2.9K) - 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) (👨‍💻 390 · 🔀 1.3K · 📦 5.6K · 📋 5K - 11% open · ⏱️ 23.04.2025): ``` git clone https://github.com/mne-tools/mne-python ``` - [PyPi](https://pypi.org/project/mne) (📥 170K / month · 📦 420 · ⏱️ 18.12.2024): ``` pip install mne ``` - [Conda](https://anaconda.org/conda-forge/mne) (📥 520K · ⏱️ 22.04.2025): ``` conda install -c conda-forge mne ``` </details> <details><summary><b><a href="https://github.com/nilearn/nilearn">Nilearn</a></b> (🥇38 · ⭐ 1.3K · 📉) - 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) (👨‍💻 250 · 🔀 600 · 📥 300 · 📦 4.1K · 📋 2.3K - 12% open · ⏱️ 24.04.2025): ``` git clone https://github.com/nilearn/nilearn ``` - [PyPi](https://pypi.org/project/nilearn) (📥 120K / month · 📦 310 · ⏱️ 23.12.2024): ``` pip install nilearn ``` - [Conda](https://anaconda.org/conda-forge/nilearn) (📥 330K · ⏱️ 22.04.2025): ``` conda install -c conda-forge nilearn ``` </details> <details><summary><b><a href="https://github.com/Project-MONAI/MONAI">MONAI</a></b> (🥈36 · ⭐ 6.3K) - 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) (👨‍💻 220 · 🔀 1.2K · 📦 4K · 📋 3.2K - 12% open · ⏱️ 13.04.2025): ``` git clone https://github.com/Project-MONAI/MONAI ``` - [PyPi](https://pypi.org/project/monai) (📥 260K / month · 📦 140 · ⏱️ 10.12.2024): ``` pip install monai ``` - [Conda](https://anaconda.org/conda-forge/monai) (📥 47K · ⏱️ 22.04.2025): ``` conda install -c conda-forge monai ``` </details> <details><summary><b><a href="https://github.com/nipy/nipype">NIPYPE</a></b> (🥈35 · ⭐ 780) - Workflows and interfaces for neuroimaging packages. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/nipy/nipype) (👨‍💻 260 · 🔀 530 · 📦 6.5K · 📋 1.4K - 30% open · ⏱️ 19.03.2025): ``` git clone https://github.com/nipy/nipype ``` - [PyPi](https://pypi.org/project/nipype) (📥 350K / month · 📦 150 · ⏱️ 19.03.2025): ``` pip install nipype ``` - [Conda](https://anaconda.org/conda-forge/nipype) (📥 790K · ⏱️ 22.04.2025): ``` conda install -c conda-forge nipype ``` </details> <details><summary><b><a href="https://github.com/nipy/nibabel">NiBabel</a></b> (🥈34 · ⭐ 700) - 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) (👨‍💻 110 · 🔀 260 · 📦 28K · 📋 550 - 23% open · ⏱️ 18.03.2025): ``` git clone https://github.com/nipy/nibabel ``` - [PyPi](https://pypi.org/project/nibabel) (📥 790K / month · 📦 1.2K · ⏱️ 23.10.2024): ``` pip install nibabel ``` - [Conda](https://anaconda.org/conda-forge/nibabel) (📥 890K · ⏱️ 22.04.2025): ``` conda install -c conda-forge nibabel ``` </details> <details><summary><b><a href="https://github.com/CamDavidsonPilon/lifelines">Lifelines</a></b> (🥈33 · ⭐ 2.4K) - Survival analysis in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/CamDavidsonPilon/lifelines) (👨‍💻 120 · 🔀 560 · 📦 3.8K · 📋 980 - 27% open · ⏱️ 29.10.2024): ``` git clone https://github.com/CamDavidsonPilon/lifelines ``` - [PyPi](https://pypi.org/project/lifelines) (📥 2.8M / month · 📦 160 · ⏱️ 29.10.2024): ``` pip install lifelines ``` - [Conda](https://anaconda.org/conda-forge/lifelines) (📥 420K · ⏱️ 22.04.2025): ``` conda install -c conda-forge lifelines ``` </details> <details><summary><b><a href="https://github.com/hail-is/hail">Hail</a></b> (🥈33 · ⭐ 1K) - 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) (👨‍💻 97 · 🔀 250 · 📦 160 · 📋 2.5K - 10% open · ⏱️ 23.04.2025): ``` git clone https://github.com/hail-is/hail ``` - [PyPi](https://pypi.org/project/hail) (📥 23K / month · 📦 42 · ⏱️ 07.03.2025): ``` pip install hail ``` </details> <details><summary><b><a href="https://github.com/google/deepvariant">DeepVariant</a></b> (🥉24 · ⭐ 3.4K) - 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) (👨‍💻 36 · 🔀 730 · 📥 4.8K · 📋 900 - 0% open · ⏱️ 10.03.2025): ``` git clone https://github.com/google/deepvariant ``` - [Conda](https://anaconda.org/bioconda/deepvariant) (📥 76K · ⏱️ 22.04.2025): ``` conda install -c bioconda deepvariant ``` </details> <details><summary><b><a href="https://github.com/brainiak/brainiak">Brainiak</a></b> (🥉19 · ⭐ 350) - Brain Imaging Analysis Kit. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/brainiak/brainiak) (👨‍💻 35 · 🔀 140 · 📋 230 - 38% open · ⏱️ 06.01.2025): ``` git clone https://github.com/brainiak/brainiak ``` - [PyPi](https://pypi.org/project/brainiak) (📥 2.4K / month · ⏱️ 07.01.2025): ``` pip install brainiak ``` - [Docker Hub](https://hub.docker.com/r/brainiak/brainiak) (📥 1.9K · ⭐ 1 · ⏱️ 07.01.2025): ``` docker pull brainiak/brainiak ``` </details> <details><summary>Show 10 hidden projects...</summary> - <b><a href="https://github.com/dipy/dipy">DIPY</a></b> (🥈33 · ⭐ 760) - DIPY is the paragon 3D/4D+ medical imaging library in Python... <code>❗Unlicensed</code> - <b><a href="https://github.com/NifTK/NiftyNet">NiftyNet</a></b> (🥉25 · ⭐ 1.4K · 💀) - [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/nipy/nipy">NIPY</a></b> (🥉24 · ⭐ 390) - Neuroimaging in Python FMRI analysis package. <code>❗Unlicensed</code> - <b><a href="https://github.com/loli/medpy">MedPy</a></b> (🥉23 · ⭐ 600 · 💤) - Medical image processing in Python. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/DLTK/DLTK">DLTK</a></b> (🥉20 · ⭐ 1.4K · 💀) - 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/projectglow/glow">Glow</a></b> (🥉20 · ⭐ 280) - 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/perone/medicaltorch">MedicalTorch</a></b> (🥉15 · ⭐ 870 · 💀) - 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/QTIM-Lab/DeepNeuro">DeepNeuro</a></b> (🥉15 · ⭐ 130 · 💀) - 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/MIC-DKFZ/medicaldetectiontoolkit">Medical Detection Toolkit</a></b> (🥉14 · ⭐ 1.3K · 💀) - 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/Tencent/MedicalNet">MedicalNet</a></b> (🥉12 · ⭐ 2K · 💀) - 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> (🥇24 · ⭐ 1.5K) - 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) (👨‍💻 27 · 🔀 150 · 📥 54 · 📋 170 - 6% open · ⏱️ 19.04.2025): ``` git clone https://github.com/manujosephv/pytorch_tabular ``` - [PyPi](https://pypi.org/project/pytorch_tabular) (📥 7.3K / month · 📦 9 · ⏱️ 28.11.2024): ``` pip install pytorch_tabular ``` </details> <details><summary><b><a href="https://github.com/AnotherSamWilson/miceforest">miceforest</a></b> (🥇24 · ⭐ 380 · 💤) - Multiple Imputation with LightGBM in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/AnotherSamWilson/miceforest) (👨‍💻 8 · 🔀 30 · 📦 230 · 📋 90 - 11% open · ⏱️ 02.08.2024): ``` git clone https://github.com/AnotherSamWilson/miceforest ``` - [PyPi](https://pypi.org/project/miceforest) (📥 74K / month · 📦 9 · ⏱️ 02.08.2024): ``` pip install miceforest ``` - [Conda](https://anaconda.org/conda-forge/miceforest) (📥 19K · ⏱️ 22.04.2025): ``` conda install -c conda-forge miceforest ``` </details> <details><summary><b><a href="https://github.com/upgini/upgini">upgini</a></b> (🥉22 · ⭐ 330) - 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) (👨‍💻 13 · 🔀 25 · 📦 9 · ⏱️ 19.04.2025): ``` git clone https://github.com/upgini/upgini ``` - [PyPi](https://pypi.org/project/upgini) (📥 28K / month · ⏱️ 24.04.2025): ``` pip install upgini ``` </details> <details><summary>Show 2 hidden projects...</summary> - <b><a href="https://github.com/carefree0910/carefree-learn">carefree-learn</a></b> (🥉18 · ⭐ 410 · 💀) - 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> - <b><a href="https://github.com/firmai/deltapy">deltapy</a></b> (🥉13 · ⭐ 540 · 💀) - 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> (🥇41 · ⭐ 49K) - 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) (👨‍💻 280 · 🔀 8.1K · 📥 1.8M · 📦 5.2K · 📋 9.6K - 0% open · ⏱️ 22.04.2025): ``` git clone https://github.com/PaddlePaddle/PaddleOCR ``` - [PyPi](https://pypi.org/project/paddleocr) (📥 360K / month · 📦 140 · ⏱️ 07.03.2025): ``` pip install paddleocr ``` </details> <details><summary><b><a href="https://github.com/ocrmypdf/OCRmyPDF">OCRmyPDF</a></b> (🥇38 · ⭐ 28K · 📈) - OCRmyPDF adds an OCR text layer to scanned PDF files, allowing.. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code></summary> - [GitHub](https://github.com/ocrmypdf/OCRmyPDF) (👨‍💻 110 · 🔀 1.9K · 📥 11K · 📦 1.3K · 📋 1.2K - 10% open · ⏱️ 21.04.2025): ``` git clone https://github.com/ocrmypdf/OCRmyPDF ``` - [PyPi](https://pypi.org/project/ocrmypdf) (📥 240K / month · 📦 46 · ⏱️ 24.04.2025): ``` pip install ocrmypdf ``` - [Conda](https://anaconda.org/conda-forge/ocrmypdf) (📥 96K · ⏱️ 22.04.2025): ``` conda install -c conda-forge ocrmypdf ``` </details> <details><summary><b><a href="https://github.com/JaidedAI/EasyOCR">EasyOCR</a></b> (🥈34 · ⭐ 26K · 💤) - Ready-to-use OCR with 80+ supported languages and all popular.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/JaidedAI/EasyOCR) (👨‍💻 130 · 🔀 3.3K · 📥 20M · 📦 14K · 📋 1.1K - 43% open · ⏱️ 24.09.2024): ``` git clone https://github.com/JaidedAI/EasyOCR ``` - [PyPi](https://pypi.org/project/easyocr) (📥 850K / month · 📦 250 · ⏱️ 24.09.2024): ``` pip install easyocr ``` </details> <details><summary><b><a href="https://github.com/madmaze/pytesseract">Tesseract</a></b> (🥈31 · ⭐ 6.1K) - 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) (👨‍💻 50 · 🔀 720 · 📋 370 - 3% open · ⏱️ 17.02.2025): ``` git clone https://github.com/madmaze/pytesseract ``` - [PyPi](https://pypi.org/project/pytesseract) (📥 3.1M / month · 📦 970 · ⏱️ 16.08.2024): ``` pip install pytesseract ``` - [Conda](https://anaconda.org/conda-forge/pytesseract) (📥 660K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pytesseract ``` </details> <details><summary><b><a href="https://github.com/sirfz/tesserocr">tesserocr</a></b> (🥈31 · ⭐ 2.1K) - 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) (👨‍💻 31 · 🔀 260 · 📥 940 · 📦 1.2K · 📋 280 - 17% open · ⏱️ 12.02.2025): ``` git clone https://github.com/sirfz/tesserocr ``` - [PyPi](https://pypi.org/project/tesserocr) (📥 120K / month · 📦 43 · ⏱️ 12.02.2025): ``` pip install tesserocr ``` - [Conda](https://anaconda.org/conda-forge/tesserocr) (📥 250K · ⏱️ 22.04.2025): ``` conda install -c conda-forge tesserocr ``` </details> <details><summary><b><a href="https://github.com/open-mmlab/mmocr">MMOCR</a></b> (🥉27 · ⭐ 4.5K) - 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) (👨‍💻 90 · 🔀 750 · 📦 220 · 📋 930 - 20% open · ⏱️ 27.11.2024): ``` git clone https://github.com/open-mmlab/mmocr ``` - [PyPi](https://pypi.org/project/mmocr) (📥 4.8K / month · 📦 4 · ⏱️ 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> (🥉26 · ⭐ 1.4K · 💀) - 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> (🥉24 · ⭐ 1.1K) - Line based ATR Engine based on OCRopy. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/WZBSocialScienceCenter/pdftabextract">pdftabextract</a></b> (🥉21 · ⭐ 2.2K · 💀) - 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> (🥉21 · ⭐ 1.1K · 💀) - 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> (🥉20 · ⭐ 1.3K · 💀) - 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> (🥉10 · ⭐ 660 · 💀) - 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._ 🔗&nbsp;<b><a href="https://github.com/ml-tooling/best-of-python#data-containers--dataframes">best-of-python - Data Containers</a></b> ( ⭐ 3.9K) - 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._ 🔗&nbsp;<b><a href="https://github.com/ml-tooling/best-of-python#data-loading--extraction">best-of-python - Data Extraction</a></b> ( ⭐ 3.9K) - 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._ 🔗&nbsp;<b><a href="https://github.com/ml-tooling/best-of-web-python#web-scraping--crawling">best-of-web-python - Web Scraping</a></b> ( ⭐ 2.5K · 💤) - 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._ 🔗&nbsp;<b><a href="https://github.com/ml-tooling/best-of-python#data-pipelines--streaming">best-of-python - Data Pipelines</a></b> ( ⭐ 3.9K) - Libraries for data batch- and stream-processing,.. <details><summary>Show 1 hidden projects...</summary> - <b><a href="https://github.com/clugen/pyclugen">pyclugen</a></b> (🥇10 · ⭐ 8) - Multidimensional cluster generation in Python. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> </details> <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> (🥇47 · ⭐ 37K) - 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) (👨‍💻 1.2K · 🔀 6.2K · 📥 250 · 📦 23K · 📋 21K - 21% open · ⏱️ 24.04.2025): ``` git clone https://github.com/ray-project/ray ``` - [PyPi](https://pypi.org/project/ray) (📥 6.7M / month · 📦 920 · ⏱️ 27.03.2025): ``` pip install ray ``` - [Conda](https://anaconda.org/conda-forge/ray-tune) (📥 740K · ⏱️ 22.04.2025): ``` conda install -c conda-forge ray-tune ``` </details> <details><summary><b><a href="https://github.com/dask/dask">dask</a></b> (🥇44 · ⭐ 13K) - Parallel computing with task scheduling. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/dask/dask) (👨‍💻 620 · 🔀 1.8K · 📦 73K · 📋 5.5K - 20% open · ⏱️ 24.04.2025): ``` git clone https://github.com/dask/dask ``` - [PyPi](https://pypi.org/project/dask) (📥 11M / month · 📦 2.9K · ⏱️ 22.04.2025): ``` pip install dask ``` - [Conda](https://anaconda.org/conda-forge/dask) (📥 13M · ⏱️ 22.04.2025): ``` conda install -c conda-forge dask ``` </details> <details><summary><b><a href="https://github.com/deepspeedai/DeepSpeed">DeepSpeed</a></b> (🥇41 · ⭐ 38K) - 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/deepspeedai/DeepSpeed) (👨‍💻 380 · 🔀 4.3K · 📦 13K · 📋 3.1K - 33% open · ⏱️ 23.04.2025): ``` git clone https://github.com/microsoft/DeepSpeed ``` - [PyPi](https://pypi.org/project/deepspeed) (📥 670K / month · 📦 270 · ⏱️ 18.04.2025): ``` pip install deepspeed ``` - [Docker Hub](https://hub.docker.com/r/deepspeed/deepspeed) (📥 22K · ⭐ 4 · ⏱️ 02.09.2022): ``` docker pull deepspeed/deepspeed ``` </details> <details><summary><b><a href="https://github.com/dask/distributed">dask.distributed</a></b> (🥇39 · ⭐ 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) (👨‍💻 340 · 🔀 730 · 📦 40K · 📋 4K - 38% open · ⏱️ 22.04.2025): ``` git clone https://github.com/dask/distributed ``` - [PyPi](https://pypi.org/project/distributed) (📥 3.9M / month · 📦 960 · ⏱️ 22.04.2025): ``` pip install distributed ``` - [Conda](https://anaconda.org/conda-forge/distributed) (📥 17M · ⏱️ 22.04.2025): ``` conda install -c conda-forge distributed ``` </details> <details><summary><b><a href="https://github.com/Lightning-AI/torchmetrics">metrics</a></b> (🥈36 · ⭐ 2.3K) - 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) (👨‍💻 270 · 🔀 420 · 📥 6.5K · 📦 41K · 📋 940 - 7% open · ⏱️ 23.04.2025): ``` git clone https://github.com/Lightning-AI/metrics ``` - [PyPi](https://pypi.org/project/metrics) (📥 6.5K / month · 📦 4 · ⏱️ 26.02.2025): ``` pip install metrics ``` - [Conda](https://anaconda.org/conda-forge/torchmetrics) (📥 1.9M · ⏱️ 22.04.2025): ``` conda install -c conda-forge torchmetrics ``` </details> <details><summary><b><a href="https://github.com/horovod/horovod">horovod</a></b> (🥈35 · ⭐ 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) (👨‍💻 170 · 🔀 2.3K · 📦 1.4K · 📋 2.3K - 17% open · ⏱️ 01.02.2025): ``` git clone https://github.com/horovod/horovod ``` - [PyPi](https://pypi.org/project/horovod) (📥 93K / month · 📦 34 · ⏱️ 12.06.2023): ``` pip install horovod ``` </details> <details><summary><b><a href="https://github.com/h2oai/h2o-3">H2O-3</a></b> (🥈35 · ⭐ 7.1K) - 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) (👨‍💻 280 · 🔀 2K · 📦 98 · 📋 9.6K - 30% open · ⏱️ 11.04.2025): ``` git clone https://github.com/h2oai/h2o-3 ``` - [PyPi](https://pypi.org/project/h2o) (📥 190K / month · 📦 55 · ⏱️ 27.03.2025): ``` pip install h2o ``` </details> <details><summary><b><a href="https://github.com/hpcaitech/ColossalAI">ColossalAI</a></b> (🥈32 · ⭐ 41K) - 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) (👨‍💻 200 · 🔀 4.5K · 📦 500 · 📋 1.8K - 26% open · ⏱️ 18.04.2025): ``` git clone https://github.com/hpcaitech/colossalai ``` </details> <details><summary><b><a href="https://github.com/intel/ipex-llm">BigDL</a></b> (🥈32 · ⭐ 7.8K) - 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/ipex-llm) (👨‍💻 120 · 🔀 1.3K · 📥 680 · 📋 2.9K - 39% open · ⏱️ 24.04.2025): ``` git clone https://github.com/intel-analytics/BigDL ``` - [PyPi](https://pypi.org/project/bigdl) (📥 27K / month · 📦 2 · ⏱️ 24.03.2024): ``` pip install bigdl ``` - [Maven](https://search.maven.org/artifact/com.intel.analytics.bigdl/bigdl-SPARK_2.4) (📦 5 · ⏱️ 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> (🥈32 · ⭐ 3.3K) - PyTorch extensions for high performance and large scale training. <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) (👨‍💻 76 · 🔀 290 · 📦 8.1K · 📋 390 - 26% open · ⏱️ 12.01.2025): ``` git clone https://github.com/facebookresearch/fairscale ``` - [PyPi](https://pypi.org/project/fairscale) (📥 520K / month · 📦 150 · ⏱️ 11.12.2022): ``` pip install fairscale ``` - [Conda](https://anaconda.org/conda-forge/fairscale) (📥 440K · ⏱️ 22.04.2025): ``` conda install -c conda-forge fairscale ``` </details> <details><summary><b><a href="https://github.com/mpi4py/mpi4py">mpi4py</a></b> (🥈31 · ⭐ 850) - Python bindings for MPI. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/mpi4py/mpi4py) (👨‍💻 27 · 🔀 120 · 📥 32K · 📋 200 - 2% open · ⏱️ 23.04.2025): ``` git clone https://github.com/mpi4py/mpi4py ``` - [PyPi](https://pypi.org/project/mpi4py) (📥 420K / month · 📦 830 · ⏱️ 13.02.2025): ``` pip install mpi4py ``` - [Conda](https://anaconda.org/conda-forge/mpi4py) (📥 3.7M · ⏱️ 22.04.2025): ``` conda install -c conda-forge mpi4py ``` </details> <details><summary><b><a href="https://github.com/microsoft/SynapseML">SynapseML</a></b> (🥈30 · ⭐ 5.1K) - Simple and Distributed Machine Learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/microsoft/SynapseML) (👨‍💻 120 · 🔀 840 · 📋 800 - 49% open · ⏱️ 19.04.2025): ``` git clone https://github.com/microsoft/SynapseML ``` - [PyPi](https://pypi.org/project/synapseml) (📥 590K / month · 📦 7 · ⏱️ 17.04.2025): ``` pip install synapseml ``` </details> <details><summary><b><a href="https://github.com/dask/dask-ml">dask-ml</a></b> (🥈29 · ⭐ 930) - Scalable Machine Learning with Dask. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/dask/dask-ml) (👨‍💻 80 · 🔀 260 · 📦 1.2K · 📋 550 - 51% open · ⏱️ 07.02.2025): ``` git clone https://github.com/dask/dask-ml ``` - [PyPi](https://pypi.org/project/dask-ml) (📥 120K / month · 📦 100 · ⏱️ 08.02.2025): ``` pip install dask-ml ``` - [Conda](https://anaconda.org/conda-forge/dask-ml) (📥 970K · ⏱️ 22.04.2025): ``` conda install -c conda-forge dask-ml ``` </details> <details><summary><b><a href="https://github.com/facebookincubator/submitit">Submit it</a></b> (🥉28 · ⭐ 1.4K) - 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) (👨‍💻 26 · 🔀 130 · 📦 4.3K · 📋 130 - 39% open · ⏱️ 24.04.2025): ``` git clone https://github.com/facebookincubator/submitit ``` - [PyPi](https://pypi.org/project/submitit) (📥 470K / month · 📦 49 · ⏱️ 18.09.2024): ``` pip install submitit ``` - [Conda](https://anaconda.org/conda-forge/submitit) (📥 56K · ⏱️ 22.04.2025): ``` conda install -c conda-forge submitit ``` </details> <details><summary><b><a href="https://github.com/learning-at-home/hivemind">Hivemind</a></b> (🥉27 · ⭐ 2.2K · 📈) - 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) (👨‍💻 34 · 🔀 180 · 📦 130 · 📋 190 - 43% open · ⏱️ 19.04.2025): ``` git clone https://github.com/learning-at-home/hivemind ``` - [PyPi](https://pypi.org/project/hivemind) (📥 4.3K / month · 📦 12 · ⏱️ 20.04.2025): ``` pip install hivemind ``` </details> <details><summary><b><a href="https://github.com/apache/singa">Apache Singa</a></b> (🥉25 · ⭐ 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) (👨‍💻 97 · 🔀 1.3K · 📦 5 · 📋 140 - 35% open · ⏱️ 26.03.2025): ``` git clone https://github.com/apache/singa ``` - [Conda](https://anaconda.org/nusdbsystem/singa) (📥 980 · ⏱️ 25.03.2025): ``` conda install -c nusdbsystem singa ``` - [Docker Hub](https://hub.docker.com/r/apache/singa) (📥 9K · ⭐ 4 · ⏱️ 31.05.2022): ``` docker pull apache/singa ``` </details> <details><summary><b><a href="https://github.com/microsoft/SynapseML">MMLSpark</a></b> (🥉23 · ⭐ 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) (👨‍💻 120 · 🔀 840 · 📋 800 - 49% open · ⏱️ 19.04.2025): ``` git clone https://github.com/microsoft/SynapseML ``` - [PyPi](https://pypi.org/project/mmlspark) (⏱️ 18.03.2020): ``` pip install mmlspark ``` </details> <details><summary><b><a href="https://github.com/intel/analytics-zoo">analytics-zoo</a></b> (🥉22 · ⭐ 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-zoo) (👨‍💻 110 · 🔀 730 · 📋 1.3K - 32% open · ⏱️ 09.01.2025): ``` git clone https://github.com/intel-analytics/analytics-zoo ``` - [PyPi](https://pypi.org/project/analytics-zoo) (📥 1.4K / month · 📦 1 · ⏱️ 22.08.2022): ``` pip install analytics-zoo ``` </details> <details><summary>Show 18 hidden projects...</summary> - <b><a href="https://github.com/DEAP/deap">DEAP</a></b> (🥈34 · ⭐ 6.1K) - Distributed Evolutionary Algorithms in Python. <code><a href="http://bit.ly/37RvQcA">❗️LGPL-3.0</a></code> - <b><a href="https://github.com/ipython/ipyparallel">ipyparallel</a></b> (🥈30 · ⭐ 2.6K) - IPython Parallel: Interactive Parallel Computing in.. <code>❗Unlicensed</code> <code><img src="https://git.io/JLy1E" style="display:inline;" width="13" height="13"></code> - <b><a href="https://github.com/uber/petastorm">petastorm</a></b> (🥉28 · ⭐ 1.8K · 💀) - Petastorm library enables single machine or distributed.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/yahoo/TensorFlowOnSpark">TensorFlowOnSpark</a></b> (🥉27 · ⭐ 3.9K · 💀) - 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> (🥉25 · ⭐ 1.6K · 💀) - 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> (🥉22 · ⭐ 3.7K · 💀) - 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> (🥉22 · ⭐ 1.6K · 💀) - 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> (🥉21 · ⭐ 280 · 💀) - 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> (🥉21 · ⭐ 270 · 💀) - 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> (🥉19 · ⭐ 320 · 💀) - 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> (🥉18 · ⭐ 6.3K · 💀) - 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> (🥉18 · ⭐ 290 · 💀) - 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> (🥉17 · ⭐ 1K · 💀) - 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> (🥉17 · ⭐ 790 · 💀) - 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> (🥉15 · ⭐ 720 · 💀) - 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> (🥉15 · ⭐ 49 · 💀) - 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> (🥉12 · ⭐ 130 · 💀) - 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> (🥉11 · ⭐ 370 · 💀) - 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> (🥇43 · ⭐ 12K) - A hyperparameter optimization framework. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/optuna/optuna) (👨‍💻 290 · 🔀 1.1K · 📦 25K · 📋 1.7K - 3% open · ⏱️ 23.04.2025): ``` git clone https://github.com/optuna/optuna ``` - [PyPi](https://pypi.org/project/optuna) (📥 4M / month · 📦 1.2K · ⏱️ 14.04.2025): ``` pip install optuna ``` - [Conda](https://anaconda.org/conda-forge/optuna) (📥 2.6M · ⏱️ 22.04.2025): ``` conda install -c conda-forge optuna ``` </details> <details><summary><b><a href="https://github.com/autogluon/autogluon">AutoGluon</a></b> (🥇36 · ⭐ 8.8K) - 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) (👨‍💻 140 · 🔀 1K · 📦 1.1K · 📋 1.6K - 24% open · ⏱️ 23.04.2025): ``` git clone https://github.com/autogluon/autogluon ``` - [PyPi](https://pypi.org/project/autogluon) (📥 220K / month · 📦 31 · ⏱️ 24.04.2025): ``` pip install autogluon ``` - [Conda](https://anaconda.org/conda-forge/autogluon) (📥 33K · ⏱️ 22.04.2025): ``` conda install -c conda-forge autogluon ``` - [Docker Hub](https://hub.docker.com/r/autogluon/autogluon) (📥 16K · ⭐ 19 · ⏱️ 07.03.2024): ``` docker pull autogluon/autogluon ``` </details> <details><summary><b><a href="https://github.com/facebook/Ax">Ax</a></b> (🥇36 · ⭐ 2.5K) - 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) (👨‍💻 180 · 🔀 320 · 📦 950 · 📋 850 - 10% open · ⏱️ 24.04.2025): ``` git clone https://github.com/facebook/Ax ``` - [PyPi](https://pypi.org/project/ax-platform) (📥 150K / month · 📦 57 · ⏱️ 03.02.2025): ``` pip install ax-platform ``` - [Conda](https://anaconda.org/conda-forge/ax-platform) (📥 37K · ⏱️ 22.04.2025): ``` conda install -c conda-forge ax-platform ``` </details> <details><summary><b><a href="https://github.com/hyperopt/hyperopt">Hyperopt</a></b> (🥇34 · ⭐ 7.4K) - Distributed Asynchronous Hyperparameter Optimization in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/hyperopt/hyperopt) (👨‍💻 100 · 🔀 1.1K · 📦 21K · 📋 750 - 19% open · ⏱️ 27.12.2024): ``` git clone https://github.com/hyperopt/hyperopt ``` - [PyPi](https://pypi.org/project/hyperopt) (📥 2.3M / month · 📦 450 · ⏱️ 17.11.2021): ``` pip install hyperopt ``` - [Conda](https://anaconda.org/conda-forge/hyperopt) (📥 830K · ⏱️ 22.04.2025): ``` conda install -c conda-forge hyperopt ``` </details> <details><summary><b><a href="https://github.com/pytorch/botorch">BoTorch</a></b> (🥇34 · ⭐ 3.2K) - 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) (👨‍💻 140 · 🔀 410 · 📦 1.5K · 📋 580 - 13% open · ⏱️ 23.04.2025): ``` git clone https://github.com/pytorch/botorch ``` - [PyPi](https://pypi.org/project/botorch) (📥 210K / month · 📦 100 · ⏱️ 03.02.2025): ``` pip install botorch ``` - [Conda](https://anaconda.org/conda-forge/botorch) (📥 150K · ⏱️ 22.04.2025): ``` conda install -c conda-forge botorch ``` </details> <details><summary><b><a href="https://github.com/bayesian-optimization/BayesianOptimization">Bayesian Optimization</a></b> (🥇33 · ⭐ 8.2K) - 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) (👨‍💻 48 · 🔀 1.6K · 📥 180 · 📦 3.6K · 📋 380 - 1% open · ⏱️ 22.04.2025): ``` git clone https://github.com/fmfn/BayesianOptimization ``` - [PyPi](https://pypi.org/project/bayesian-optimization) (📥 440K / month · 📦 150 · ⏱️ 27.12.2024): ``` pip install bayesian-optimization ``` </details> <details><summary><b><a href="https://github.com/facebookresearch/nevergrad">nevergrad</a></b> (🥇33 · ⭐ 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) (👨‍💻 58 · 🔀 360 · 📦 890 · 📋 310 - 40% open · ⏱️ 23.04.2025): ``` git clone https://github.com/facebookresearch/nevergrad ``` - [PyPi](https://pypi.org/project/nevergrad) (📥 130K / month · 📦 72 · ⏱️ 23.04.2025): ``` pip install nevergrad ``` - [Conda](https://anaconda.org/conda-forge/nevergrad) (📥 61K · ⏱️ 22.04.2025): ``` conda install -c conda-forge nevergrad ``` </details> <details><summary><b><a href="https://github.com/alteryx/featuretools">featuretools</a></b> (🥈32 · ⭐ 7.4K) - 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) (👨‍💻 74 · 🔀 880 · 📦 2K · 📋 1K - 15% open · ⏱️ 13.11.2024): ``` git clone https://github.com/alteryx/featuretools ``` - [PyPi](https://pypi.org/project/featuretools) (📥 90K / month · 📦 74 · ⏱️ 14.05.2024): ``` pip install featuretools ``` - [Conda](https://anaconda.org/conda-forge/featuretools) (📥 240K · ⏱️ 22.04.2025): ``` conda install -c conda-forge featuretools ``` </details> <details><summary><b><a href="https://github.com/keras-team/autokeras">AutoKeras</a></b> (🥈31 · ⭐ 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) (👨‍💻 140 · 🔀 1.4K · 📥 19K · 📦 840 · 📋 910 - 16% open · ⏱️ 16.12.2024): ``` git clone https://github.com/keras-team/autokeras ``` - [PyPi](https://pypi.org/project/autokeras) (📥 18K / month · 📦 13 · ⏱️ 20.03.2024): ``` pip install autokeras ``` </details> <details><summary><b><a href="https://github.com/keras-team/keras-tuner">Keras Tuner</a></b> (🥈31 · ⭐ 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) (👨‍💻 61 · 🔀 400 · 📦 5.7K · 📋 500 - 44% open · ⏱️ 24.06.2024): ``` git clone https://github.com/keras-team/keras-tuner ``` - [PyPi](https://pypi.org/project/keras-tuner) (📥 350K / month · 📦 120 · ⏱️ 04.03.2024): ``` pip install keras-tuner ``` - [Conda](https://anaconda.org/conda-forge/keras-tuner) (📥 55K · ⏱️ 22.04.2025): ``` conda install -c conda-forge keras-tuner ``` </details> <details><summary><b><a href="https://github.com/mljar/mljar-supervised">mljar-supervised</a></b> (🥈29 · ⭐ 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) (👨‍💻 30 · 🔀 420 · 📦 140 · 📋 670 - 20% open · ⏱️ 14.04.2025): ``` git clone https://github.com/mljar/mljar-supervised ``` - [PyPi](https://pypi.org/project/mljar-supervised) (📥 9.5K / month · 📦 6 · ⏱️ 01.04.2025): ``` pip install mljar-supervised ``` - [Conda](https://anaconda.org/conda-forge/mljar-supervised) (📥 40K · ⏱️ 22.04.2025): ``` conda install -c conda-forge mljar-supervised ``` </details> <details><summary><b><a href="https://github.com/shankarpandala/lazypredict">lazypredict</a></b> (🥈29 · ⭐ 3.1K) - 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) (👨‍💻 18 · 🔀 360 · 📦 1.3K · 📋 140 - 70% open · ⏱️ 05.04.2025): ``` git clone https://github.com/shankarpandala/lazypredict ``` - [PyPi](https://pypi.org/project/lazypredict) (📥 21K / month · 📦 8 · ⏱️ 05.04.2025): ``` pip install lazypredict ``` - [Conda](https://anaconda.org/conda-forge/lazypredict) (📥 4.6K · ⏱️ 22.04.2025): ``` conda install -c conda-forge lazypredict ``` </details> <details><summary><b><a href="https://github.com/autonomio/talos">Talos</a></b> (🥈25 · ⭐ 1.6K · 💤) - 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) (👨‍💻 23 · 🔀 270 · 📦 200 · 📋 400 - 2% open · ⏱️ 22.04.2024): ``` git clone https://github.com/autonomio/talos ``` - [PyPi](https://pypi.org/project/talos) (📥 2K / month · 📦 8 · ⏱️ 21.04.2024): ``` pip install talos ``` </details> <details><summary><b><a href="https://github.com/aimclub/FEDOT">FEDOT</a></b> (🥈25 · ⭐ 670) - 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) (👨‍💻 38 · 🔀 88 · 📦 60 · 📋 570 - 11% open · ⏱️ 31.03.2025): ``` git clone https://github.com/nccr-itmo/FEDOT ``` - [PyPi](https://pypi.org/project/fedot) (📥 2K / month · 📦 7 · ⏱️ 10.03.2025): ``` pip install fedot ``` </details> <details><summary><b><a href="https://github.com/AutoViML/featurewiz">featurewiz</a></b> (🥉23 · ⭐ 640) - 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) (👨‍💻 18 · 🔀 95 · 📦 83 · 📋 110 - 0% open · ⏱️ 19.02.2025): ``` git clone https://github.com/AutoViML/featurewiz ``` - [PyPi](https://pypi.org/project/featurewiz) (📥 16K / month · 📦 4 · ⏱️ 19.02.2025): ``` pip install featurewiz ``` </details> <details><summary><b><a href="https://github.com/SimonBlanke/Hyperactive">Hyperactive</a></b> (🥉22 · ⭐ 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) (👨‍💻 12 · 🔀 47 · 📥 310 · 📦 37 · 📋 79 - 18% open · ⏱️ 15.04.2025): ``` git clone https://github.com/SimonBlanke/Hyperactive ``` - [PyPi](https://pypi.org/project/hyperactive) (📥 3.4K / month · 📦 13 · ⏱️ 15.08.2024): ``` pip install hyperactive ``` </details> <details><summary><b><a href="https://github.com/AutoViML/Auto_ViML">Auto ViML</a></b> (🥉21 · ⭐ 540) - Automatically Build Multiple ML Models with a Single Line of Code... <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/AutoViML/Auto_ViML) (👨‍💻 9 · 🔀 100 · 📦 28 · ⏱️ 30.01.2025): ``` git clone https://github.com/AutoViML/Auto_ViML ``` - [PyPi](https://pypi.org/project/autoviml) (📥 6.5K / month · 📦 3 · ⏱️ 30.01.2025): ``` pip install autoviml ``` </details> <details><summary><b><a href="https://github.com/ScottfreeLLC/AlphaPy">AlphaPy</a></b> (🥉20 · ⭐ 1.5K) - 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) (👨‍💻 5 · 🔀 230 · 📦 8 · 📋 44 - 34% open · ⏱️ 15.12.2024): ``` git clone https://github.com/ScottfreeLLC/AlphaPy ``` - [PyPi](https://pypi.org/project/alphapy) (📥 800 / month · ⏱️ 29.08.2020): ``` pip install alphapy ``` </details> <details><summary><b><a href="https://github.com/gugarosa/opytimizer">opytimizer</a></b> (🥉18 · ⭐ 620 · 💤) - 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) (👨‍💻 4 · 🔀 42 · 📦 21 · ⏱️ 18.08.2024): ``` git clone https://github.com/gugarosa/opytimizer ``` - [PyPi](https://pypi.org/project/opytimizer) (📥 860 / month · ⏱️ 18.08.2024): ``` pip install opytimizer ``` </details> <details><summary>Show 33 hidden projects...</summary> - <b><a href="https://github.com/EpistasisLab/tpot">TPOT</a></b> (🥇33 · ⭐ 9.9K) - A Python Automated Machine Learning tool that optimizes machine.. <code><a href="http://bit.ly/37RvQcA">❗️LGPL-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/scikit-optimize/scikit-optimize">scikit-optimize</a></b> (🥇33 · ⭐ 2.8K · 💀) - 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> (🥈31 · ⭐ 14K · 💀) - 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/automl/auto-sklearn">auto-sklearn</a></b> (🥈31 · ⭐ 7.8K · 💀) - 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> (🥈27 · ⭐ 2.2K · 💀) - 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> (🥈27 · ⭐ 1.2K) - SMAC3: A Versatile Bayesian Optimization Package for.. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">❗️BSD-1-Clause</a></code> - <b><a href="https://github.com/SheffieldML/GPyOpt">GPyOpt</a></b> (🥈25 · ⭐ 940 · 💀) - Gaussian Process Optimization using GPy. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> - <b><a href="https://github.com/mindsdb/lightwood">lightwood</a></b> (🥈25 · ⭐ 460) - Lightwood is Legos for Machine Learning. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-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/tensorflow/adanet">AdaNet</a></b> (🥉24 · ⭐ 3.5K · 💀) - 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> (🥉24 · ⭐ 1.6K · 💀) - [UNMAINTAINED] Automated machine learning for analytics & production. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/automl/HpBandSter">HpBandSter</a></b> (🥉23 · ⭐ 620 · 💀) - 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> (🥉23 · ⭐ 290 · 💀) - 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> (🥉21 · ⭐ 3.1K · 💀) - 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> (🥉21 · ⭐ 1.5K · 💀) - MLBox is a powerful Automated Machine Learning python library. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">❗️BSD-1-Clause</a></code> - <b><a href="https://github.com/rsteca/sklearn-deap">sklearn-deap</a></b> (🥉21 · ⭐ 770 · 💀) - 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> (🥉21 · ⭐ 740 · 💀) - 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> (🥉21 · ⭐ 610 · 💀) - 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> (🥉20 · ⭐ 420 · 💀) - 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> (🥉19 · ⭐ 880 · 💀) - 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> (🥉19 · ⭐ 530 · 💀) - 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> (🥉19 · ⭐ 340 · 💀) - Hyperparameter optimization that enables researchers to.. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/tobegit3hub/advisor">Advisor</a></b> (🥉18 · ⭐ 1.6K · 💀) - 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> (🥉18 · ⭐ 1.3K · 💀) - 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/cerlymarco/shap-hypetune">shap-hypetune</a></b> (🥉18 · ⭐ 580 · 💀) - A python package for simultaneous Hyperparameters Tuning and.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/HunterMcGushion/hyperparameter_hunter">HyperparameterHunter</a></b> (🥉17 · ⭐ 710 · 💀) - 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> (🥉16 · ⭐ 1.9K · 💀) - 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> (🥉15 · ⭐ 200 · 💀) - 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> (🥉13 · ⭐ 2.7K · 💀) - 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> (🥉13 · ⭐ 200 · 💀) - An automatic ML model optimization tool. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/genixpro/hypermax">Hypermax</a></b> (🥉13 · ⭐ 110 · 💀) - 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> (🥉11 · ⭐ 3.3K · 💀) - 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> (🥉11 · ⭐ 950 · 💀) - 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> (🥉10 · ⭐ 140 · 💀) - 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> (🥇32 · ⭐ 12K) - FinRL: Financial Reinforcement Learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/AI4Finance-Foundation/FinRL) (👨‍💻 120 · 🔀 2.6K · 📦 86 · 📋 740 - 34% open · ⏱️ 23.04.2025): ``` git clone https://github.com/AI4Finance-Foundation/FinRL ``` - [PyPi](https://pypi.org/project/finrl) (📥 3.1K / month · ⏱️ 08.01.2022): ``` pip install finrl ``` </details> <details><summary><b><a href="https://github.com/Farama-Foundation/ViZDoom">ViZDoom</a></b> (🥇29 · ⭐ 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) (👨‍💻 55 · 🔀 390 · 📥 12K · 📦 320 · 📋 460 - 6% open · ⏱️ 12.03.2025): ``` git clone https://github.com/mwydmuch/ViZDoom ``` - [PyPi](https://pypi.org/project/vizdoom) (📥 6K / month · 📦 15 · ⏱️ 20.08.2024): ``` pip install vizdoom ``` </details> <details><summary><b><a href="https://github.com/tensorflow/agents">TF-Agents</a></b> (🥈28 · ⭐ 2.9K) - 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) (👨‍💻 150 · 🔀 720 · 📋 680 - 30% open · ⏱️ 12.03.2025): ``` git clone https://github.com/tensorflow/agents ``` - [PyPi](https://pypi.org/project/tf-agents) (📥 35K / month · 📦 14 · ⏱️ 14.12.2023): ``` pip install tf-agents ``` </details> <details><summary><b><a href="https://github.com/google-deepmind/acme">Acme</a></b> (🥈27 · ⭐ 3.7K) - 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) (👨‍💻 87 · 🔀 460 · 📦 240 · 📋 270 - 23% open · ⏱️ 18.04.2025): ``` git clone https://github.com/deepmind/acme ``` - [PyPi](https://pypi.org/project/dm-acme) (📥 3.4K / month · 📦 3 · ⏱️ 10.02.2022): ``` pip install dm-acme ``` - [Conda](https://anaconda.org/conda-forge/dm-acme) (📥 12K · ⏱️ 22.04.2025): ``` conda install -c conda-forge dm-acme ``` </details> <details><summary><b><a href="https://github.com/google/dopamine">Dopamine</a></b> (🥈26 · ⭐ 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) (👨‍💻 15 · 🔀 1.4K · 📦 21 · 📋 190 - 54% open · ⏱️ 04.11.2024): ``` git clone https://github.com/google/dopamine ``` - [PyPi](https://pypi.org/project/dopamine-rl) (📥 30K / month · 📦 10 · ⏱️ 31.10.2024): ``` pip install dopamine-rl ``` </details> <details><summary><b><a href="https://github.com/tensorforce/tensorforce">TensorForce</a></b> (🥈26 · ⭐ 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) (👨‍💻 85 · 🔀 530 · 📦 460 · 📋 680 - 6% open · ⏱️ 31.07.2024): ``` git clone https://github.com/tensorforce/tensorforce ``` - [PyPi](https://pypi.org/project/tensorforce) (📥 720 / month · 📦 4 · ⏱️ 30.08.2021): ``` pip install tensorforce ``` </details> <details><summary><b><a href="https://github.com/PaddlePaddle/PARL">PARL</a></b> (🥉25 · ⭐ 3.4K) - 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) (👨‍💻 46 · 🔀 820 · 📦 130 · 📋 550 - 24% open · ⏱️ 24.01.2025): ``` git clone https://github.com/PaddlePaddle/PARL ``` - [PyPi](https://pypi.org/project/parl) (📥 1.3K / month · 📦 1 · ⏱️ 13.05.2022): ``` pip install parl ``` </details> <details><summary><b><a href="https://github.com/google-deepmind/rlax">RLax</a></b> (🥉24 · ⭐ 1.3K) - 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) (👨‍💻 22 · 🔀 91 · 📦 330 · 📋 27 - 33% open · ⏱️ 14.04.2025): ``` git clone https://github.com/deepmind/rlax ``` - [PyPi](https://pypi.org/project/rlax) (📥 17K / month · 📦 11 · ⏱️ 09.01.2023): ``` pip install rlax ``` </details> <details><summary><b><a href="https://github.com/pfnet/pfrl">PFRL</a></b> (🥉22 · ⭐ 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) (👨‍💻 20 · 🔀 150 · 📦 120 · 📋 79 - 41% open · ⏱️ 04.08.2024): ``` git clone https://github.com/pfnet/pfrl ``` - [PyPi](https://pypi.org/project/pfrl) (📥 370 / month · 📦 1 · ⏱️ 16.07.2023): ``` pip install pfrl ``` </details> <details><summary><b><a href="https://github.com/facebookresearch/ReAgent">ReAgent</a></b> (🥉21 · ⭐ 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) (👨‍💻 170 · 🔀 510 · 📋 160 - 53% open · ⏱️ 12.03.2025): ``` git clone https://github.com/facebookresearch/ReAgent ``` - [PyPi](https://pypi.org/project/reagent) (📥 71 / month · ⏱️ 27.05.2020): ``` pip install reagent ``` </details> <details><summary><b><a href="https://github.com/google-research/rliable">rliable</a></b> (🥉14 · ⭐ 830 · 💤) - [NeurIPS21 Outstanding Paper] Library for reliable evaluation on.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/google-research/rliable) (👨‍💻 10 · 🔀 49 · 📦 200 · 📋 20 - 15% open · ⏱️ 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> (🥇42 · ⭐ 36K · 💀) - 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> (🥈28 · ⭐ 16K · 💀) - OpenAI Baselines: high-quality implementations of reinforcement.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/tensorlayer/TensorLayer">TensorLayer</a></b> (🥈27 · ⭐ 7.4K · 💀) - 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/keras-rl/keras-rl">keras-rl</a></b> (🥈27 · ⭐ 5.5K · 💀) - 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/rlworkgroup/garage">garage</a></b> (🥉25 · ⭐ 2K · 💀) - 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> (🥉24 · ⭐ 4.3K · 💀) - 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> (🥉24 · ⭐ 1.2K · 💀) - 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> (🥉22 · ⭐ 3.1K · 💀) - 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> (🥉21 · ⭐ 2.3K · 💀) - 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> (🥉19 · ⭐ 6.9K · 💀) - 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> (🥉17 · ⭐ 7.2K · 💀) - A customisable 3D platform for agent-based AI research. <code>❗Unlicensed</code> - <b><a href="https://github.com/enlite-ai/maze">Maze</a></b> (🥉13 · ⭐ 280 · 💀) - Maze Applied Reinforcement Learning Framework. <code><a href="https://tldrlegal.com/search?q=Custom">❗️Custom</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> (🥇33 · ⭐ 20K) - Best Practices on Recommendation Systems. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/recommenders-team/recommenders) (👨‍💻 140 · 🔀 3.2K · 📥 730 · 📦 160 · 📋 880 - 18% open · ⏱️ 19.01.2025): ``` git clone https://github.com/microsoft/recommenders ``` - [PyPi](https://pypi.org/project/recommenders) (📥 21K / month · 📦 4 · ⏱️ 24.12.2024): ``` pip install recommenders ``` </details> <details><summary><b><a href="https://github.com/pytorch/torchrec">torchrec</a></b> (🥇31 · ⭐ 2.1K) - Pytorch domain library for recommendation systems. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/pytorch/torchrec) (👨‍💻 340 · 🔀 480 · 📦 200 · 📋 480 - 71% open · ⏱️ 24.04.2025): ``` git clone https://github.com/pytorch/torchrec ``` - [PyPi](https://pypi.org/project/torchrec-nightly-cpu) (📥 2.9K / month · ⏱️ 12.05.2022): ``` pip install torchrec-nightly-cpu ``` </details> <details><summary><b><a href="https://github.com/PreferredAI/cornac">Cornac</a></b> (🥈29 · ⭐ 950) - 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) (👨‍💻 24 · 🔀 150 · 📦 280 · 📋 160 - 15% open · ⏱️ 21.04.2025): ``` git clone https://github.com/PreferredAI/cornac ``` - [PyPi](https://pypi.org/project/cornac) (📥 42K / month · 📦 18 · ⏱️ 15.04.2025): ``` pip install cornac ``` - [Conda](https://anaconda.org/conda-forge/cornac) (📥 800K · ⏱️ 22.04.2025): ``` conda install -c conda-forge cornac ``` </details> <details><summary><b><a href="https://github.com/NicolasHug/Surprise">scikit-surprise</a></b> (🥈28 · ⭐ 6.6K · 💤) - 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) (👨‍💻 46 · 🔀 1K · 📦 21 · 📋 400 - 21% open · ⏱️ 14.06.2024): ``` git clone https://github.com/NicolasHug/Surprise ``` - [PyPi](https://pypi.org/project/scikit-surprise) (📥 160K / month · 📦 37 · ⏱️ 19.05.2024): ``` pip install scikit-surprise ``` - [Conda](https://anaconda.org/conda-forge/scikit-surprise) (📥 480K · ⏱️ 22.04.2025): ``` conda install -c conda-forge scikit-surprise ``` </details> <details><summary><b><a href="https://github.com/RUCAIBox/RecBole">RecBole</a></b> (🥉27 · ⭐ 3.7K) - 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) (👨‍💻 79 · 🔀 660 · 📋 1K - 29% open · ⏱️ 24.02.2025): ``` git clone https://github.com/RUCAIBox/RecBole ``` - [PyPi](https://pypi.org/project/recbole) (📥 58K / month · 📦 2 · ⏱️ 24.02.2025): ``` pip install recbole ``` - [Conda](https://anaconda.org/aibox/recbole) (📥 8K · ⏱️ 25.03.2025): ``` conda install -c aibox recbole ``` </details> <details><summary><b><a href="https://github.com/tensorflow/recommenders">TF Recommenders</a></b> (🥉24 · ⭐ 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) (👨‍💻 43 · 🔀 290 · 📋 450 - 59% open · ⏱️ 16.01.2025): ``` git clone https://github.com/tensorflow/recommenders ``` - [PyPi](https://pypi.org/project/tensorflow-recommenders) (📥 260K / month · 📦 2 · ⏱️ 03.02.2023): ``` pip install tensorflow-recommenders ``` </details> <details><summary>Show 11 hidden projects...</summary> - <b><a href="https://github.com/benfred/implicit">implicit</a></b> (🥈30 · ⭐ 3.7K · 💀) - 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> (🥈29 · ⭐ 4.9K · 💀) - 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> (🥈28 · ⭐ 290) - Python recommendation toolkit. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/tensorflow/ranking">TF Ranking</a></b> (🥉26 · ⭐ 2.8K · 💀) - 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> - <b><a href="https://github.com/ibayer/fastFM">fastFM</a></b> (🥉22 · ⭐ 1.1K · 💀) - 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> (🥉21 · ⭐ 1.3K · 💀) - 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/maciejkula/spotlight">Spotlight</a></b> (🥉19 · ⭐ 3K · 💀) - 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/statisticianinstilettos/recmetrics">recmetrics</a></b> (🥉19 · ⭐ 580 · 💀) - A library of metrics for evaluating recommender systems. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/caserec/CaseRecommender">Case Recommender</a></b> (🥉18 · ⭐ 500 · 💀) - 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/ylongqi/openrec">OpenRec</a></b> (🥉17 · ⭐ 420 · 💀) - OpenRec is an open-source and modular library for neural network-.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/ShopRunner/collie">Collie</a></b> (🥉17 · ⭐ 110 · 💀) - 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> </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> (🥇36 · ⭐ 9.7K) - 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) (👨‍💻 520 · 🔀 2K · 📥 1.9K · 📦 1 · 📋 3.4K - 1% open · ⏱️ 13.04.2025): ``` git clone https://github.com/OpenMined/PySyft ``` - [PyPi](https://pypi.org/project/syft) (📥 13K / month · 📦 5 · ⏱️ 13.04.2025): ``` pip install syft ``` </details> <details><summary><b><a href="https://github.com/pytorch/opacus">Opacus</a></b> (🥈32 · ⭐ 1.8K) - 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) (👨‍💻 85 · 🔀 360 · 📥 140 · 📦 1.1K · 📋 330 - 20% open · ⏱️ 10.04.2025): ``` git clone https://github.com/pytorch/opacus ``` - [PyPi](https://pypi.org/project/opacus) (📥 92K / month · 📦 42 · ⏱️ 18.02.2025): ``` pip install opacus ``` - [Conda](https://anaconda.org/conda-forge/opacus) (📥 23K · ⏱️ 22.04.2025): ``` conda install -c conda-forge opacus ``` </details> <details><summary><b><a href="https://github.com/tensorflow/privacy">TensorFlow Privacy</a></b> (🥈25 · ⭐ 2K) - 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) (👨‍💻 60 · 🔀 450 · 📥 190 · 📋 210 - 55% open · ⏱️ 23.04.2025): ``` git clone https://github.com/tensorflow/privacy ``` - [PyPi](https://pypi.org/project/tensorflow-privacy) (📥 22K / month · 📦 21 · ⏱️ 14.02.2024): ``` pip install tensorflow-privacy ``` </details> <details><summary><b><a href="https://github.com/tf-encrypted/tf-encrypted">TFEncrypted</a></b> (🥈25 · ⭐ 1.2K · 💤) - A Framework for Encrypted Machine Learning 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/tf-encrypted/tf-encrypted) (👨‍💻 29 · 🔀 210 · 📦 68 · 📋 440 - 32% open · ⏱️ 25.09.2024): ``` git clone https://github.com/tf-encrypted/tf-encrypted ``` - [PyPi](https://pypi.org/project/tf-encrypted) (📥 2K / month · 📦 9 · ⏱️ 16.11.2022): ``` pip install tf-encrypted ``` </details> <details><summary><b><a href="https://github.com/facebookresearch/CrypTen">CrypTen</a></b> (🥉24 · ⭐ 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) (👨‍💻 39 · 🔀 280 · 📦 57 · 📋 280 - 28% open · ⏱️ 23.11.2024): ``` git clone https://github.com/facebookresearch/CrypTen ``` - [PyPi](https://pypi.org/project/crypten) (📥 770 / month · 📦 1 · ⏱️ 08.12.2022): ``` pip install crypten ``` </details> <details><summary><b><a href="https://github.com/FederatedAI/FATE">FATE</a></b> (🥉23 · ⭐ 5.9K) - An Industrial Grade Federated Learning Framework. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/FederatedAI/FATE) (👨‍💻 100 · 🔀 1.6K · 📋 2.1K - 3% open · ⏱️ 19.11.2024): ``` git clone https://github.com/FederatedAI/FATE ``` - [PyPi](https://pypi.org/project/ETAF) (⏱️ 06.05.2020): ``` pip install ETAF ``` </details> <details><summary>Show 1 hidden projects...</summary> - <b><a href="https://github.com/OpenMined/PipelineDP">PipelineDP</a></b> (🥉19 · ⭐ 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> (🥇44 · ⭐ 20K) - 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) (👨‍💻 840 · 🔀 4.5K · 📦 58K · 📋 4.6K - 39% open · ⏱️ 24.04.2025): ``` git clone https://github.com/mlflow/mlflow ``` - [PyPi](https://pypi.org/project/mlflow) (📥 16M / month · 📦 1.1K · ⏱️ 24.04.2025): ``` pip install mlflow ``` - [Conda](https://anaconda.org/conda-forge/mlflow) (📥 3.1M · ⏱️ 22.04.2025): ``` conda install -c conda-forge mlflow ``` </details> <details><summary><b><a href="https://github.com/tensorflow/tensorboard">Tensorboard</a></b> (🥇43 · ⭐ 6.9K) - 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) (👨‍💻 320 · 🔀 1.7K · 📦 310K · 📋 1.9K - 35% open · ⏱️ 16.04.2025): ``` git clone https://github.com/tensorflow/tensorboard ``` - [PyPi](https://pypi.org/project/tensorboard) (📥 26M / month · 📦 2.5K · ⏱️ 12.02.2025): ``` pip install tensorboard ``` - [Conda](https://anaconda.org/conda-forge/tensorboard) (📥 5.5M · ⏱️ 22.04.2025): ``` conda install -c conda-forge tensorboard ``` </details> <details><summary><b><a href="https://github.com/wandb/wandb">wandb client</a></b> (🥇42 · ⭐ 9.8K) - 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) (👨‍💻 210 · 🔀 730 · 📥 690 · 📦 75K · 📋 3.6K - 17% open · ⏱️ 23.04.2025): ``` git clone https://github.com/wandb/client ``` - [PyPi](https://pypi.org/project/wandb) (📥 17M / month · 📦 1.8K · ⏱️ 22.04.2025): ``` pip install wandb ``` - [Conda](https://anaconda.org/conda-forge/wandb) (📥 1M · ⏱️ 23.04.2025): ``` conda install -c conda-forge wandb ``` </details> <details><summary><b><a href="https://github.com/iterative/dvc">DVC</a></b> (🥇41 · ⭐ 14K) - Data Versioning and ML Experiments. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/iterative/dvc) (👨‍💻 310 · 🔀 1.2K · 📦 23K · 📋 4.8K - 5% open · ⏱️ 24.04.2025): ``` git clone https://github.com/iterative/dvc ``` - [PyPi](https://pypi.org/project/dvc) (📥 790K / month · 📦 140 · ⏱️ 15.02.2025): ``` pip install dvc ``` - [Conda](https://anaconda.org/conda-forge/dvc) (📥 2.8M · ⏱️ 22.04.2025): ``` conda install -c conda-forge dvc ``` </details> <details><summary><b><a href="https://github.com/aws/sagemaker-python-sdk">SageMaker SDK</a></b> (🥈40 · ⭐ 2.2K) - 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) (👨‍💻 480 · 🔀 1.2K · 📦 5.8K · 📋 1.6K - 20% open · ⏱️ 23.04.2025): ``` git clone https://github.com/aws/sagemaker-python-sdk ``` - [PyPi](https://pypi.org/project/sagemaker) (📥 23M / month · 📦 180 · ⏱️ 23.04.2025): ``` pip install sagemaker ``` - [Conda](https://anaconda.org/conda-forge/sagemaker-python-sdk) (📥 1.5M · ⏱️ 22.04.2025): ``` conda install -c conda-forge sagemaker-python-sdk ``` </details> <details><summary><b><a href="https://github.com/pycaret/pycaret">PyCaret</a></b> (🥈36 · ⭐ 9.3K) - 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) (👨‍💻 140 · 🔀 1.8K · 📥 730 · 📦 7.5K · 📋 2.3K - 16% open · ⏱️ 06.03.2025): ``` git clone https://github.com/pycaret/pycaret ``` - [PyPi](https://pypi.org/project/pycaret) (📥 340K / month · 📦 31 · ⏱️ 28.04.2024): ``` pip install pycaret ``` - [Conda](https://anaconda.org/conda-forge/pycaret) (📥 68K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pycaret ``` </details> <details><summary><b><a href="https://github.com/Netflix/metaflow">Metaflow</a></b> (🥈36 · ⭐ 8.7K) - Build, Manage and Deploy AI/ML Systems. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/Netflix/metaflow) (👨‍💻 100 · 🔀 820 · 📦 890 · 📋 790 - 42% open · ⏱️ 22.04.2025): ``` git clone https://github.com/Netflix/metaflow ``` - [PyPi](https://pypi.org/project/metaflow) (📥 290K / month · 📦 52 · ⏱️ 22.04.2025): ``` pip install metaflow ``` - [Conda](https://anaconda.org/conda-forge/metaflow) (📥 290K · ⏱️ 22.04.2025): ``` conda install -c conda-forge metaflow ``` </details> <details><summary><b><a href="https://github.com/clearml/clearml">ClearML</a></b> (🥈34 · ⭐ 6K) - 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/clearml/clearml) (👨‍💻 100 · 🔀 670 · 📥 3.2K · 📦 1.7K · 📋 1.1K - 43% open · ⏱️ 24.04.2025): ``` git clone https://github.com/allegroai/clearml ``` - [PyPi](https://pypi.org/project/clearml) (📥 360K / month · 📦 55 · ⏱️ 20.04.2025): ``` pip install clearml ``` - [Docker Hub](https://hub.docker.com/r/allegroai/trains) (📥 30K · ⏱️ 05.10.2020): ``` docker pull allegroai/trains ``` </details> <details><summary><b><a href="https://github.com/snakemake/snakemake">snakemake</a></b> (🥈34 · ⭐ 2.5K) - 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) (👨‍💻 370 · 🔀 590 · 📦 2.3K · 📋 2K - 60% open · ⏱️ 24.04.2025): ``` git clone https://github.com/snakemake/snakemake ``` - [PyPi](https://pypi.org/project/snakemake) (📥 76K / month · 📦 280 · ⏱️ 24.04.2025): ``` pip install snakemake ``` - [Conda](https://anaconda.org/bioconda/snakemake) (📥 1.4M · ⏱️ 22.04.2025): ``` conda install -c bioconda snakemake ``` </details> <details><summary><b><a href="https://github.com/lanpa/tensorboardX">tensorboardX</a></b> (🥈33 · ⭐ 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) (👨‍💻 85 · 🔀 860 · 📥 480 · 📦 57K · 📋 460 - 17% open · ⏱️ 24.04.2025): ``` git clone https://github.com/lanpa/tensorboardX ``` - [PyPi](https://pypi.org/project/tensorboardX) (📥 2.8M / month · 📦 620 · ⏱️ 20.08.2023): ``` pip install tensorboardX ``` - [Conda](https://anaconda.org/conda-forge/tensorboardx) (📥 1.3M · ⏱️ 22.04.2025): ``` conda install -c conda-forge tensorboardx ``` </details> <details><summary><b><a href="https://github.com/Kaggle/kaggle-api">kaggle</a></b> (🥈33 · ⭐ 6.6K) - Official Kaggle API. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/Kaggle/kaggle-api) (👨‍💻 49 · 🔀 1.2K · 📦 21 · 📋 520 - 28% open · ⏱️ 22.04.2025): ``` git clone https://github.com/Kaggle/kaggle-api ``` - [PyPi](https://pypi.org/project/kaggle) (📥 360K / month · 📦 230 · ⏱️ 14.03.2025): ``` pip install kaggle ``` - [Conda](https://anaconda.org/conda-forge/kaggle) (📥 220K · ⏱️ 22.04.2025): ``` conda install -c conda-forge kaggle ``` </details> <details><summary><b><a href="https://github.com/aimhubio/aim">aim</a></b> (🥈33 · ⭐ 5.5K) - 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) (👨‍💻 82 · 🔀 340 · 📦 860 · 📋 1.1K - 36% open · ⏱️ 08.04.2025): ``` git clone https://github.com/aimhubio/aim ``` - [PyPi](https://pypi.org/project/aim) (📥 180K / month · 📦 41 · ⏱️ 23.04.2025): ``` pip install aim ``` - [Conda](https://anaconda.org/conda-forge/aim) (📥 120K · ⏱️ 22.04.2025): ``` conda install -c conda-forge aim ``` </details> <details><summary><b><a href="https://github.com/IDSIA/sacred">sacred</a></b> (🥈31 · ⭐ 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) (👨‍💻 110 · 🔀 380 · 📦 3.5K · 📋 560 - 18% open · ⏱️ 26.11.2024): ``` git clone https://github.com/IDSIA/sacred ``` - [PyPi](https://pypi.org/project/sacred) (📥 30K / month · 📦 60 · ⏱️ 26.11.2024): ``` pip install sacred ``` - [Conda](https://anaconda.org/conda-forge/sacred) (📥 8.6K · ⏱️ 22.04.2025): ``` conda install -c conda-forge sacred ``` </details> <details><summary><b><a href="https://github.com/Azure/MachineLearningNotebooks">AzureML SDK</a></b> (🥈31 · ⭐ 4.2K) - 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) (👨‍💻 65 · 🔀 2.5K · 📥 660 · 📋 1.5K - 26% open · ⏱️ 14.03.2025): ``` git clone https://github.com/Azure/MachineLearningNotebooks ``` - [PyPi](https://pypi.org/project/azureml-sdk) (📥 270K / month · 📦 31 · ⏱️ 11.04.2025): ``` pip install azureml-sdk ``` </details> <details><summary><b><a href="https://github.com/neptune-ai/neptune-client">Neptune.ai</a></b> (🥈30 · ⭐ 610) - 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) (👨‍💻 55 · 🔀 65 · 📦 840 · 📋 260 - 12% open · ⏱️ 16.04.2025): ``` git clone https://github.com/neptune-ai/neptune-client ``` - [PyPi](https://pypi.org/project/neptune-client) (📥 490K / month · 📦 77 · ⏱️ 15.04.2025): ``` pip install neptune-client ``` - [Conda](https://anaconda.org/conda-forge/neptune-client) (📥 340K · ⏱️ 22.04.2025): ``` conda install -c conda-forge neptune-client ``` </details> <details><summary><b><a href="https://github.com/google/ml-metadata">ml-metadata</a></b> (🥈28 · ⭐ 640) - 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) (👨‍💻 23 · 🔀 160 · 📥 3K · 📦 690 · 📋 120 - 39% open · ⏱️ 03.04.2025): ``` git clone https://github.com/google/ml-metadata ``` - [PyPi](https://pypi.org/project/ml-metadata) (📥 94K / month · 📦 32 · ⏱️ 07.04.2025): ``` pip install ml-metadata ``` </details> <details><summary><b><a href="https://github.com/PaddlePaddle/VisualDL">VisualDL</a></b> (🥉27 · ⭐ 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) (👨‍💻 36 · 🔀 630 · 📥 510 · 📦 2 · 📋 510 - 30% open · ⏱️ 22.01.2025): ``` git clone https://github.com/PaddlePaddle/VisualDL ``` - [PyPi](https://pypi.org/project/visualdl) (📥 160K / month · 📦 82 · ⏱️ 30.10.2024): ``` pip install visualdl ``` </details> <details><summary><b><a href="https://github.com/stared/livelossplot">livelossplot</a></b> (🥉27 · ⭐ 1.3K) - 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></summary> - [GitHub](https://github.com/stared/livelossplot) (👨‍💻 17 · 🔀 140 · 📦 1.8K · 📋 79 - 7% open · ⏱️ 03.01.2025): ``` git clone https://github.com/stared/livelossplot ``` - [PyPi](https://pypi.org/project/livelossplot) (📥 20K / month · 📦 16 · ⏱️ 03.01.2025): ``` pip install livelossplot ``` </details> <details><summary><b><a href="https://github.com/labmlai/labml">Labml</a></b> (🥉26 · ⭐ 2.2K) - 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) (👨‍💻 9 · 🔀 140 · 📦 220 · 📋 50 - 12% open · ⏱️ 10.04.2025): ``` git clone https://github.com/labmlai/labml ``` - [PyPi](https://pypi.org/project/labml) (📥 5.1K / month · 📦 14 · ⏱️ 15.09.2024): ``` pip install labml ``` </details> <details><summary><b><a href="https://github.com/mrpowers-io/quinn">quinn</a></b> (🥉26 · ⭐ 670) - 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) (👨‍💻 31 · 🔀 97 · 📥 57 · 📦 91 · 📋 130 - 27% open · ⏱️ 06.12.2024): ``` git clone https://github.com/MrPowers/quinn ``` - [PyPi](https://pypi.org/project/quinn) (📥 670K / month · 📦 7 · ⏱️ 13.02.2024): ``` pip install quinn ``` </details> <details><summary><b><a href="https://github.com/pytorch/tnt">TNT</a></b> (🥉25 · ⭐ 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) (👨‍💻 150 · 🔀 280 · 📋 150 - 56% open · ⏱️ 11.04.2025): ``` git clone https://github.com/pytorch/tnt ``` - [PyPi](https://pypi.org/project/torchnet) (📥 5.8K / month · 📦 24 · ⏱️ 29.07.2018): ``` pip install torchnet ``` </details> <details><summary><b><a href="https://github.com/m3dev/gokart">gokart</a></b> (🥉25 · ⭐ 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) (👨‍💻 47 · 🔀 62 · 📦 84 · 📋 99 - 32% open · ⏱️ 24.04.2025): ``` git clone https://github.com/m3dev/gokart ``` - [PyPi](https://pypi.org/project/gokart) (📥 6K / month · 📦 8 · ⏱️ 27.02.2025): ``` pip install gokart ``` </details> <details><summary><b><a href="https://github.com/replicate/keepsake">keepsake</a></b> (🥉19 · ⭐ 1.7K) - Version control for machine learning. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/replicate/keepsake) (👨‍💻 18 · 🔀 71 · 📋 190 - 66% open · ⏱️ 03.12.2024): ``` git clone https://github.com/replicate/keepsake ``` - [PyPi](https://pypi.org/project/keepsake) (📥 220 / month · 📦 1 · ⏱️ 25.01.2021): ``` pip install keepsake ``` </details> <details><summary><b><a href="https://www.comet.com">CometML</a></b> (🥉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) (📥 520K / month · 📦 94 · ⏱️ 17.04.2025): ``` 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> (🥈28 · ⭐ 3.3K · 💀) - 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> (🥉26 · ⭐ 2.8K · 💀) - 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/EducationalTestingService/skll">SKLL</a></b> (🥉24 · ⭐ 550) - SciKit-Learn Laboratory (SKLL) makes it easy to run machine.. <code>❗Unlicensed</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> (🥉23 · ⭐ 880 · 💀) - 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> (🥉22 · ⭐ 1.8K · 💀) - 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> (🥉22 · ⭐ 380 · 💀) - Studio: Simplify and expedite model building process. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/microsoft/tensorwatch">TensorWatch</a></b> (🥉21 · ⭐ 3.4K · 💀) - Debugging, monitoring and visualization for Python Machine.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/instacart/lore">lore</a></b> (🥉21 · ⭐ 1.6K · 💀) - 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> (🥉21 · ⭐ 630 · 💀) - Log TensorBoard events without touching TensorFlow. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/awslabs/mxboard">MXBoard</a></b> (🥉20 · ⭐ 320 · 💀) - 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> (🥉18 · ⭐ 340 · 💀) - 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> (🥉18 · ⭐ 230 · 💤) - A multi-functional library for full-stack Deep Learning... <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/minerva-ml/steppy">steppy</a></b> (🥉17 · ⭐ 130 · 💀) - Lightweight, Python library for fast and reproducible experimentation. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/google/caliban">caliban</a></b> (🥉16 · ⭐ 500 · 💀) - Research workflows made easy, locally and in the Cloud. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/ModelChimp/modelchimp">ModelChimp</a></b> (🥉13 · ⭐ 130 · 💀) - 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> (🥉10 · ⭐ 12 · 💀) - 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/triton-lang/triton">triton</a></b> (🥇43 · ⭐ 15K) - 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) (👨‍💻 390 · 🔀 1.9K · 📦 63K · 📋 1.7K - 42% open · ⏱️ 24.04.2025): ``` git clone https://github.com/openai/triton ``` - [PyPi](https://pypi.org/project/triton) (📥 23M / month · 📦 400 · ⏱️ 09.04.2025): ``` pip install triton ``` </details> <details><summary><b><a href="https://github.com/onnx/onnx">onnx</a></b> (🥇42 · ⭐ 19K) - Open standard for machine learning interoperability. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/onnx/onnx) (👨‍💻 340 · 🔀 3.7K · 📥 23K · 📦 44K · 📋 3K - 11% open · ⏱️ 23.04.2025): ``` git clone https://github.com/onnx/onnx ``` - [PyPi](https://pypi.org/project/onnx) (📥 7M / month · 📦 1.3K · ⏱️ 01.10.2024): ``` pip install onnx ``` - [Conda](https://anaconda.org/conda-forge/onnx) (📥 1.7M · ⏱️ 22.04.2025): ``` conda install -c conda-forge onnx ``` </details> <details><summary><b><a href="https://github.com/huggingface/huggingface_hub">huggingface_hub</a></b> (🥈38 · ⭐ 2.5K) - 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) (👨‍💻 230 · 🔀 670 · 📋 1.1K - 14% open · ⏱️ 24.04.2025): ``` git clone https://github.com/huggingface/huggingface_hub ``` - [PyPi](https://pypi.org/project/huggingface_hub) (📥 79M / month · 📦 2.8K · ⏱️ 08.04.2025): ``` pip install huggingface_hub ``` - [Conda](https://anaconda.org/conda-forge/huggingface_hub) (📥 3.1M · ⏱️ 22.04.2025): ``` conda install -c conda-forge huggingface_hub ``` </details> <details><summary><b><a href="https://github.com/bentoml/BentoML">BentoML</a></b> (🥈35 · ⭐ 7.6K) - 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) (👨‍💻 250 · 🔀 840 · 📥 470 · 📦 2.6K · 📋 1.1K - 12% open · ⏱️ 23.04.2025): ``` git clone https://github.com/bentoml/BentoML ``` - [PyPi](https://pypi.org/project/bentoml) (📥 110K / month · 📦 40 · ⏱️ 22.04.2025): ``` pip install bentoml ``` </details> <details><summary><b><a href="https://github.com/apple/coremltools">Core ML Tools</a></b> (🥈35 · ⭐ 4.7K) - 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) (👨‍💻 190 · 🔀 660 · 📥 14K · 📦 4.8K · 📋 1.5K - 24% open · ⏱️ 24.04.2025): ``` git clone https://github.com/apple/coremltools ``` - [PyPi](https://pypi.org/project/coremltools) (📥 420K / month · 📦 87 · ⏱️ 21.01.2025): ``` pip install coremltools ``` - [Conda](https://anaconda.org/conda-forge/coremltools) (📥 95K · ⏱️ 22.04.2025): ``` conda install -c conda-forge coremltools ``` </details> <details><summary><b><a href="https://github.com/pytorch/serve">TorchServe</a></b> (🥈33 · ⭐ 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) (👨‍💻 220 · 🔀 880 · 📥 7.7K · 📦 860 · 📋 1.7K - 25% open · ⏱️ 17.03.2025): ``` git clone https://github.com/pytorch/serve ``` - [PyPi](https://pypi.org/project/torchserve) (📥 91K / month · 📦 24 · ⏱️ 30.09.2024): ``` pip install torchserve ``` - [Conda](https://anaconda.org/pytorch/torchserve) (📥 490K · ⏱️ 25.03.2025): ``` conda install -c pytorch torchserve ``` - [Docker Hub](https://hub.docker.com/r/pytorch/torchserve) (📥 1.4M · ⭐ 32 · ⏱️ 30.09.2024): ``` docker pull pytorch/torchserve ``` </details> <details><summary><b><a href="https://github.com/fastmachinelearning/hls4ml">hls4ml</a></b> (🥈30 · ⭐ 1.5K) - 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) (👨‍💻 68 · 🔀 440 · 📦 47 · 📋 470 - 42% open · ⏱️ 16.04.2025): ``` git clone https://github.com/fastmachinelearning/hls4ml ``` - [PyPi](https://pypi.org/project/hls4ml) (📥 2.3K / month · 📦 1 · ⏱️ 17.03.2025): ``` pip install hls4ml ``` - [Conda](https://anaconda.org/conda-forge/hls4ml) (📥 10K · ⏱️ 22.04.2025): ``` conda install -c conda-forge hls4ml ``` </details> <details><summary><b><a href="https://github.com/microsoft/hummingbird">Hummingbird</a></b> (🥈25 · ⭐ 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) (👨‍💻 40 · 🔀 280 · 📥 810 · 📋 330 - 20% open · ⏱️ 24.10.2024): ``` git clone https://github.com/microsoft/hummingbird ``` - [PyPi](https://pypi.org/project/hummingbird-ml) (📥 8.6K / month · 📦 7 · ⏱️ 25.10.2024): ``` pip install hummingbird-ml ``` - [Conda](https://anaconda.org/conda-forge/hummingbird-ml) (📥 58K · ⏱️ 22.04.2025): ``` conda install -c conda-forge hummingbird-ml ``` </details> <details><summary><b><a href="https://github.com/nebuly-ai/optimate">nebullvm</a></b> (🥉21 · ⭐ 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) (👨‍💻 40 · 🔀 630 · 📋 200 - 49% open · ⏱️ 22.07.2024): ``` git clone https://github.com/nebuly-ai/nebullvm ``` - [PyPi](https://pypi.org/project/nebullvm) (📥 1K / month · 📦 2 · ⏱️ 18.06.2023): ``` pip install nebullvm ``` </details> <details><summary><b><a href="https://github.com/riga/tfdeploy">tfdeploy</a></b> (🥉17 · ⭐ 350) - 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) (👨‍💻 4 · 🔀 38 · 📋 34 - 32% open · ⏱️ 04.01.2025): ``` git clone https://github.com/riga/tfdeploy ``` - [PyPi](https://pypi.org/project/tfdeploy) (📥 730 / month · ⏱️ 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> (🥈25 · ⭐ 5.8K · 💀) - 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> (🥈25 · ⭐ 2.9K · 💀) - 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/nok/sklearn-porter">sklearn-porter</a></b> (🥉24 · ⭐ 1.3K · 💀) - 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/cortexlabs/cortex">cortex</a></b> (🥉22 · ⭐ 8K · 💀) - Production infrastructure for machine learning at scale. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/cog-imperial/OMLT">OMLT</a></b> (🥉21 · ⭐ 310) - Represent trained machine learning models as Pyomo optimization.. <code>❗Unlicensed</code> - <b><a href="https://github.com/larq/compute-engine">Larq Compute Engine</a></b> (🥉20 · ⭐ 250) - 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> (🥉19 · ⭐ 860 · 💀) - 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> (🥉19 · ⭐ 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> (🥉15 · ⭐ 240 · 💀) - 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> (🥉13 · ⭐ 2.6K · 💀) - Reference implementation of the Transformer.. <code>❗Unlicensed</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> (🥇42 · ⭐ 24K) - 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) (👨‍💻 270 · 🔀 3.4K · 📦 30K · 📋 2.6K - 25% open · ⏱️ 22.04.2025): ``` git clone https://github.com/slundberg/shap ``` - [PyPi](https://pypi.org/project/shap) (📥 7.4M / month · 📦 960 · ⏱️ 17.04.2025): ``` pip install shap ``` - [Conda](https://anaconda.org/conda-forge/shap) (📥 5.8M · ⏱️ 22.04.2025): ``` conda install -c conda-forge shap ``` </details> <details><summary><b><a href="https://github.com/arviz-devs/arviz">arviz</a></b> (🥇36 · ⭐ 1.7K) - 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) (👨‍💻 170 · 🔀 430 · 📥 180 · 📦 10K · 📋 890 - 21% open · ⏱️ 22.04.2025): ``` git clone https://github.com/arviz-devs/arviz ``` - [PyPi](https://pypi.org/project/arviz) (📥 2M / month · 📦 360 · ⏱️ 06.03.2025): ``` pip install arviz ``` - [Conda](https://anaconda.org/conda-forge/arviz) (📥 2.3M · ⏱️ 22.04.2025): ``` conda install -c conda-forge arviz ``` </details> <details><summary><b><a href="https://github.com/lutzroeder/netron">Netron</a></b> (🥇35 · ⭐ 30K) - 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) (👨‍💻 2 · 🔀 2.9K · 📥 50K · 📦 13 · 📋 1.2K - 1% open · ⏱️ 23.04.2025): ``` git clone https://github.com/lutzroeder/netron ``` - [PyPi](https://pypi.org/project/netron) (📥 43K / month · 📦 86 · ⏱️ 16.04.2025): ``` pip install netron ``` </details> <details><summary><b><a href="https://github.com/interpretml/interpret">InterpretML</a></b> (🥇34 · ⭐ 6.5K) - 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) (👨‍💻 48 · 🔀 740 · 📦 880 · 📋 470 - 22% open · ⏱️ 17.04.2025): ``` git clone https://github.com/interpretml/interpret ``` - [PyPi](https://pypi.org/project/interpret) (📥 190K / month · 📦 53 · ⏱️ 26.03.2025): ``` pip install interpret ``` </details> <details><summary><b><a href="https://github.com/pytorch/captum">Captum</a></b> (🥇34 · ⭐ 5.2K) - 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) (👨‍💻 130 · 🔀 510 · 📦 3.1K · 📋 600 - 42% open · ⏱️ 09.04.2025): ``` git clone https://github.com/pytorch/captum ``` - [PyPi](https://pypi.org/project/captum) (📥 290K / month · 📦 170 · ⏱️ 27.03.2025): ``` pip install captum ``` - [Conda](https://anaconda.org/conda-forge/captum) (📥 120K · ⏱️ 22.04.2025): ``` conda install -c conda-forge captum ``` </details> <details><summary><b><a href="https://github.com/MAIF/shapash">shapash</a></b> (🥈31 · ⭐ 2.9K) - 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) (👨‍💻 41 · 🔀 340 · 📦 190 · 📋 230 - 18% open · ⏱️ 22.04.2025): ``` git clone https://github.com/MAIF/shapash ``` - [PyPi](https://pypi.org/project/shapash) (📥 12K / month · 📦 4 · ⏱️ 20.03.2025): ``` pip install shapash ``` </details> <details><summary><b><a href="https://github.com/oegedijk/explainerdashboard">explainerdashboard</a></b> (🥈31 · ⭐ 2.4K) - 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) (👨‍💻 21 · 🔀 330 · 📦 620 · 📋 240 - 15% open · ⏱️ 29.12.2024): ``` git clone https://github.com/oegedijk/explainerdashboard ``` - [PyPi](https://pypi.org/project/explainerdashboard) (📥 72K / month · 📦 13 · ⏱️ 29.12.2024): ``` pip install explainerdashboard ``` - [Conda](https://anaconda.org/conda-forge/explainerdashboard) (📥 64K · ⏱️ 22.04.2025): ``` conda install -c conda-forge explainerdashboard ``` </details> <details><summary><b><a href="https://github.com/huggingface/evaluate">evaluate</a></b> (🥈31 · ⭐ 2.2K) - 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) (👨‍💻 130 · 🔀 270 · 📦 20K · 📋 370 - 61% open · ⏱️ 10.01.2025): ``` git clone https://github.com/huggingface/evaluate ``` - [PyPi](https://pypi.org/project/evaluate) (📥 2.8M / month · 📦 400 · ⏱️ 11.09.2024): ``` pip install evaluate ``` </details> <details><summary><b><a href="https://github.com/fairlearn/fairlearn">fairlearn</a></b> (🥈30 · ⭐ 2.1K) - A Python package to assess and improve fairness of machine.. <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) (👨‍💻 100 · 🔀 450 · 📦 3 · 📋 540 - 28% open · ⏱️ 13.04.2025): ``` git clone https://github.com/fairlearn/fairlearn ``` - [PyPi](https://pypi.org/project/fairlearn) (📥 140K / month · 📦 63 · ⏱️ 11.12.2024): ``` pip install fairlearn ``` - [Conda](https://anaconda.org/conda-forge/fairlearn) (📥 44K · ⏱️ 22.04.2025): ``` conda install -c conda-forge fairlearn ``` </details> <details><summary><b><a href="https://github.com/bmabey/pyLDAvis">pyLDAvis</a></b> (🥈30 · ⭐ 1.8K · 💤) - 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) (👨‍💻 42 · 🔀 360 · 📦 7.2K · 📋 190 - 40% open · ⏱️ 29.04.2024): ``` git clone https://github.com/bmabey/pyLDAvis ``` - [PyPi](https://pypi.org/project/pyldavis) (📥 140K / month · 📦 100 · ⏱️ 23.04.2023): ``` pip install pyldavis ``` - [Conda](https://anaconda.org/conda-forge/pyldavis) (📥 94K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pyldavis ``` </details> <details><summary><b><a href="https://github.com/py-why/dowhy">DoWhy</a></b> (🥈28 · ⭐ 7.4K) - 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) (👨‍💻 100 · 🔀 940 · 📥 43 · 📦 580 · 📋 490 - 27% open · ⏱️ 21.04.2025): ``` git clone https://github.com/py-why/dowhy ``` - [PyPi](https://pypi.org/project/dowhy) (📥 47K / month · 📦 18 · ⏱️ 24.11.2024): ``` pip install dowhy ``` - [Conda](https://anaconda.org/conda-forge/dowhy) (📥 42K · ⏱️ 22.04.2025): ``` conda install -c conda-forge dowhy ``` </details> <details><summary><b><a href="https://github.com/PAIR-code/lit">LIT</a></b> (🥈28 · ⭐ 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) (👨‍💻 38 · 🔀 360 · 📦 45 · 📋 210 - 57% open · ⏱️ 20.12.2024): ``` git clone https://github.com/PAIR-code/lit ``` - [PyPi](https://pypi.org/project/lit-nlp) (📥 6.9K / month · 📦 3 · ⏱️ 20.12.2024): ``` pip install lit-nlp ``` - [Conda](https://anaconda.org/conda-forge/lit-nlp) (📥 110K · ⏱️ 22.04.2025): ``` conda install -c conda-forge lit-nlp ``` </details> <details><summary><b><a href="https://github.com/parrt/dtreeviz">dtreeviz</a></b> (🥈28 · ⭐ 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) (👨‍💻 27 · 🔀 340 · 📦 1.5K · 📋 210 - 34% open · ⏱️ 06.03.2025): ``` git clone https://github.com/parrt/dtreeviz ``` - [PyPi](https://pypi.org/project/dtreeviz) (📥 110K / month · 📦 53 · ⏱️ 07.07.2022): ``` pip install dtreeviz ``` - [Conda](https://anaconda.org/conda-forge/dtreeviz) (📥 100K · ⏱️ 22.04.2025): ``` conda install -c conda-forge dtreeviz ``` </details> <details><summary><b><a href="https://github.com/Trusted-AI/AIF360">Fairness 360</a></b> (🥈27 · ⭐ 2.6K) - 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) (👨‍💻 73 · 🔀 840 · 📦 650 · 📋 300 - 65% open · ⏱️ 10.12.2024): ``` git clone https://github.com/Trusted-AI/AIF360 ``` - [PyPi](https://pypi.org/project/aif360) (📥 34K / month · 📦 32 · ⏱️ 08.04.2024): ``` pip install aif360 ``` - [Conda](https://anaconda.org/conda-forge/aif360) (📥 22K · ⏱️ 22.04.2025): ``` conda install -c conda-forge aif360 ``` </details> <details><summary><b><a href="https://github.com/tensorflow/model-analysis">Model Analysis</a></b> (🥈27 · ⭐ 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) (👨‍💻 59 · 🔀 280 · 📋 97 - 39% open · ⏱️ 31.03.2025): ``` git clone https://github.com/tensorflow/model-analysis ``` - [PyPi](https://pypi.org/project/tensorflow-model-analysis) (📥 90K / month · 📦 19 · ⏱️ 05.12.2024): ``` pip install tensorflow-model-analysis ``` </details> <details><summary><b><a href="https://github.com/microsoft/responsible-ai-toolbox">responsible-ai-widgets</a></b> (🥉25 · ⭐ 1.5K) - 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) (👨‍💻 43 · 🔀 390 · 📋 320 - 26% open · ⏱️ 07.02.2025): ``` git clone https://github.com/microsoft/responsible-ai-toolbox ``` - [PyPi](https://pypi.org/project/raiwidgets) (📥 9K / month · 📦 6 · ⏱️ 08.07.2024): ``` pip install raiwidgets ``` </details> <details><summary><b><a href="https://github.com/csinva/imodels">imodels</a></b> (🥉25 · ⭐ 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) (👨‍💻 25 · 🔀 120 · 📦 110 · 📋 95 - 38% open · ⏱️ 05.03.2025): ``` git clone https://github.com/csinva/imodels ``` - [PyPi](https://pypi.org/project/imodels) (📥 33K / month · 📦 9 · ⏱️ 15.10.2024): ``` pip install imodels ``` </details> <details><summary><b><a href="https://github.com/Trusted-AI/AIX360">Explainability 360</a></b> (🥉24 · ⭐ 1.7K) - 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) (👨‍💻 42 · 🔀 300 · 📦 120 · 📋 86 - 62% open · ⏱️ 26.02.2025): ``` git clone https://github.com/Trusted-AI/AIX360 ``` - [PyPi](https://pypi.org/project/aix360) (📥 1.1K / month · 📦 1 · ⏱️ 31.07.2023): ``` pip install aix360 ``` </details> <details><summary><b><a href="https://github.com/philipperemy/keract">keract</a></b> (🥉24 · ⭐ 1.1K) - 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></summary> - [GitHub](https://github.com/philipperemy/keract) (👨‍💻 17 · 🔀 190 · 📦 250 · 📋 89 - 3% open · ⏱️ 07.04.2025): ``` git clone https://github.com/philipperemy/keract ``` - [PyPi](https://pypi.org/project/keract) (📥 6.5K / month · 📦 7 · ⏱️ 07.04.2025): ``` pip install keract ``` </details> <details><summary><b><a href="https://github.com/dssg/aequitas">aequitas</a></b> (🥉24 · ⭐ 720) - Bias Auditing & Fair ML Toolkit. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/dssg/aequitas) (👨‍💻 23 · 🔀 120 · 📦 190 · 📋 99 - 51% open · ⏱️ 25.03.2025): ``` git clone https://github.com/dssg/aequitas ``` - [PyPi](https://pypi.org/project/aequitas) (📥 23K / month · 📦 8 · ⏱️ 30.01.2024): ``` pip install aequitas ``` </details> <details><summary><b><a href="https://github.com/jalammar/ecco">ecco</a></b> (🥉23 · ⭐ 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) (👨‍💻 12 · 🔀 170 · 📥 140 · 📦 33 · 📋 64 - 51% open · ⏱️ 15.08.2024): ``` git clone https://github.com/jalammar/ecco ``` - [PyPi](https://pypi.org/project/ecco) (📥 1.1K / month · 📦 1 · ⏱️ 09.01.2022): ``` pip install ecco ``` - [Conda](https://anaconda.org/conda-forge/ecco) (📥 6.6K · ⏱️ 22.04.2025): ``` conda install -c conda-forge ecco ``` </details> <details><summary><b><a href="https://github.com/parrt/random-forest-importances">random-forest-importances</a></b> (🥉22 · ⭐ 610) - 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) (👨‍💻 16 · 🔀 130 · 📦 180 · 📋 39 - 20% open · ⏱️ 24.03.2025): ``` git clone https://github.com/parrt/random-forest-importances ``` - [PyPi](https://pypi.org/project/rfpimp) (📥 13K / month · 📦 5 · ⏱️ 28.01.2021): ``` pip install rfpimp ``` </details> <details><summary><b><a href="https://github.com/interpretml/DiCE">DiCE</a></b> (🥉20 · ⭐ 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) (👨‍💻 19 · 🔀 200 · 📋 180 - 48% open · ⏱️ 22.11.2024): ``` git clone https://github.com/interpretml/DiCE ``` - [PyPi](https://pypi.org/project/dice-ml) (📥 36K / month · 📦 6 · ⏱️ 27.10.2023): ``` pip install dice-ml ``` </details> <details><summary><b><a href="https://github.com/aerdem4/lofo-importance">LOFO</a></b> (🥉20 · ⭐ 830) - Leave One Feature Out Importance. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/aerdem4/lofo-importance) (👨‍💻 6 · 🔀 87 · 📦 40 · 📋 30 - 13% open · ⏱️ 14.02.2025): ``` git clone https://github.com/aerdem4/lofo-importance ``` - [PyPi](https://pypi.org/project/lofo-importance) (📥 2.4K / month · 📦 5 · ⏱️ 14.02.2025): ``` pip install lofo-importance ``` </details> <details><summary><b><a href="https://github.com/tensorflow/fairness-indicators">fairness-indicators</a></b> (🥉19 · ⭐ 350) - 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) (👨‍💻 36 · 🔀 81 · 📋 39 - 74% open · ⏱️ 22.01.2025): ``` git clone https://github.com/tensorflow/fairness-indicators ``` - [PyPi](https://pypi.org/project/fairness-indicators) (📥 2.8K / month · ⏱️ 22.01.2025): ``` pip install fairness-indicators ``` </details> <details><summary><b><a href="https://github.com/explainX/explainx">ExplainX.ai</a></b> (🥉16 · ⭐ 430 · 💤) - 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) (👨‍💻 5 · 🔀 55 · 📥 20 · 📋 39 - 25% open · ⏱️ 21.08.2024): ``` git clone https://github.com/explainX/explainx ``` - [PyPi](https://pypi.org/project/explainx) (📥 1.6K / month · ⏱️ 04.02.2021): ``` pip install explainx ``` </details> <details><summary>Show 29 hidden projects...</summary> - <b><a href="https://github.com/marcotcr/lime">Lime</a></b> (🥇33 · ⭐ 12K · 💀) - 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/DistrictDataLabs/yellowbrick">yellowbrick</a></b> (🥈28 · ⭐ 4.3K · 💀) - 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/deepchecks/deepchecks">Deep Checks</a></b> (🥈28 · ⭐ 3.8K) - Deepchecks: Tests for Continuous Validation of ML Models &.. <code><a href="http://bit.ly/3pwmjO5">❗️AGPL-3.0</a></code> - <b><a href="https://github.com/TeamHG-Memex/eli5">eli5</a></b> (🥈28 · ⭐ 2.8K · 💀) - 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/reiinakano/scikit-plot">scikit-plot</a></b> (🥈28 · ⭐ 2.4K · 💀) - 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> (🥈27 · ⭐ 1.4K) - moDel Agnostic Language for Exploration and eXplanation. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/albermax/innvestigate">iNNvestigate</a></b> (🥈27 · ⭐ 1.3K · 💀) - 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/SeldonIO/alibi">Alibi</a></b> (🥉26 · ⭐ 2.5K) - Algorithms for explaining machine learning models. <code><a href="https://tldrlegal.com/search?q=Intel">❗️Intel</a></code> - <b><a href="https://github.com/tensorflow/lucid">Lucid</a></b> (🥉25 · ⭐ 4.7K · 💀) - 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/marcotcr/checklist">checklist</a></b> (🥉25 · ⭐ 2K · 💀) - 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/raghakot/keras-vis">keras-vis</a></b> (🥉24 · ⭐ 3K · 💀) - 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/mckinsey/causalnex">CausalNex</a></b> (🥉24 · ⭐ 2.3K · 💀) - 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> - <b><a href="https://github.com/PAIR-code/what-if-tool">What-If Tool</a></b> (🥉23 · ⭐ 950 · 💀) - Source code/webpage/demos for the What-If Tool. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/andosa/treeinterpreter">TreeInterpreter</a></b> (🥉23 · ⭐ 760 · 💀) - 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/sicara/tf-explain">tf-explain</a></b> (🥉22 · ⭐ 1K · 💀) - 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/understandable-machine-intelligence-lab/Quantus">Quantus</a></b> (🥉22 · ⭐ 600) - Quantus is an eXplainable AI toolkit for responsible evaluation of.. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/kundajelab/deeplift">deeplift</a></b> (🥉21 · ⭐ 850 · 💀) - Public facing deeplift repo. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/tensorflow/tcav">tcav</a></b> (🥉20 · ⭐ 640 · 💀) - 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> (🥉19 · ⭐ 1.2K · 💀) - XAI - An eXplainability toolbox for machine learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/tensorflow/model-card-toolkit">model-card-toolkit</a></b> (🥉18 · ⭐ 430 · 💀) - A toolkit that streamlines and automates the.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/givasile/effector">effector</a></b> (🥉18 · ⭐ 86) - Effector - a Python package for global and regional effect methods. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/edublancas/sklearn-evaluation">sklearn-evaluation</a></b> (🥉17 · ⭐ 460 · 💀) - 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/marcotcr/anchor">Anchor</a></b> (🥉16 · ⭐ 800 · 💀) - 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> (🥉16 · ⭐ 740 · 💀) - 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> (🥉15 · ⭐ 1.1K) - Python Library for Model Interpretation/Explanations. <code><a href="https://tldrlegal.com/search?q=UPL-1.0">❗️UPL-1.0</a></code> - <b><a href="https://github.com/interpretml/interpret-text">interpret-text</a></b> (🥉15 · ⭐ 420 · 💀) - 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> - <b><a href="https://github.com/suinleelab/attributionpriors">Attribution Priors</a></b> (🥉13 · ⭐ 120 · 💀) - 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/SAP-archive/contextual-ai">contextual-ai</a></b> (🥉13 · ⭐ 87 · 💀) - Contextual AI adds explainability to different stages of.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/intuit/bias-detector">bias-detector</a></b> (🥉13 · ⭐ 43 · 💀) - Bias Detector is a python package for detecting bias in machine.. <code><a href="http://bit.ly/34MBwT8">MIT</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._ 🔗&nbsp;<b><a href="https://github.com/erikbern/ann-benchmarks">ANN Benchmarks</a></b> ( ⭐ 5.2K) - Benchmarks of approximate nearest neighbor libraries in Python. <details><summary><b><a href="https://github.com/milvus-io/milvus">Milvus</a></b> (🥇42 · ⭐ 34K) - Milvus is a high-performance, cloud-native vector database built for.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/milvus-io/milvus) (👨‍💻 310 · 🔀 3.2K · 📥 340K · 📋 13K - 5% open · ⏱️ 24.04.2025): ``` git clone https://github.com/milvus-io/milvus ``` - [PyPi](https://pypi.org/project/pymilvus) (📥 1.8M / month · 📦 250 · ⏱️ 23.04.2025): ``` pip install pymilvus ``` - [Docker Hub](https://hub.docker.com/r/milvusdb/milvus) (📥 69M · ⭐ 78 · ⏱️ 24.04.2025): ``` docker pull milvusdb/milvus ``` </details> <details><summary><b><a href="https://github.com/facebookresearch/faiss">Faiss</a></b> (🥇41 · ⭐ 35K) - 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) (👨‍💻 220 · 🔀 3.8K · 📦 4.7K · 📋 2.6K - 9% open · ⏱️ 24.04.2025): ``` git clone https://github.com/facebookresearch/faiss ``` - [PyPi](https://pypi.org/project/pymilvus) (📥 1.8M / month · 📦 250 · ⏱️ 23.04.2025): ``` pip install pymilvus ``` - [Conda](https://anaconda.org/conda-forge/faiss) (📥 2.5M · ⏱️ 22.04.2025): ``` conda install -c conda-forge faiss ``` </details> <details><summary><b><a href="https://github.com/spotify/annoy">Annoy</a></b> (🥈35 · ⭐ 14K · 💤) - Approximate Nearest Neighbors in C++/Python optimized for memory.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/spotify/annoy) (👨‍💻 88 · 🔀 1.2K · 📦 5K · 📋 410 - 15% open · ⏱️ 29.07.2024): ``` git clone https://github.com/spotify/annoy ``` - [PyPi](https://pypi.org/project/annoy) (📥 800K / month · 📦 200 · ⏱️ 14.06.2023): ``` pip install annoy ``` - [Conda](https://anaconda.org/conda-forge/python-annoy) (📥 670K · ⏱️ 22.04.2025): ``` conda install -c conda-forge python-annoy ``` </details> <details><summary><b><a href="https://github.com/nmslib/hnswlib">hnswlib</a></b> (🥈32 · ⭐ 4.7K · 💤) - Header-only C++/python library for fast approximate nearest.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/nmslib/hnswlib) (👨‍💻 72 · 🔀 680 · 📦 7.9K · 📋 420 - 60% open · ⏱️ 17.06.2024): ``` git clone https://github.com/nmslib/hnswlib ``` - [PyPi](https://pypi.org/project/hnswlib) (📥 480K / month · 📦 130 · ⏱️ 03.12.2023): ``` pip install hnswlib ``` - [Conda](https://anaconda.org/conda-forge/hnswlib) (📥 350K · ⏱️ 22.04.2025): ``` conda install -c conda-forge hnswlib ``` </details> <details><summary><b><a href="https://github.com/nmslib/nmslib">NMSLIB</a></b> (🥈31 · ⭐ 3.5K · 💤) - 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) (👨‍💻 49 · 🔀 460 · 📦 1.4K · 📋 440 - 21% open · ⏱️ 21.09.2024): ``` git clone https://github.com/nmslib/nmslib ``` - [PyPi](https://pypi.org/project/nmslib) (📥 380K / month · 📦 63 · ⏱️ 03.02.2021): ``` pip install nmslib ``` - [Conda](https://anaconda.org/conda-forge/nmslib) (📥 200K · ⏱️ 22.04.2025): ``` conda install -c conda-forge nmslib ``` </details> <details><summary><b><a href="https://github.com/unum-cloud/usearch">USearch</a></b> (🥈31 · ⭐ 2.7K) - 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) (👨‍💻 70 · 🔀 180 · 📥 64K · 📦 180 · 📋 210 - 42% open · ⏱️ 16.04.2025): ``` git clone https://github.com/unum-cloud/usearch ``` - [PyPi](https://pypi.org/project/usearch) (📥 180K / month · 📦 35 · ⏱️ 16.04.2025): ``` pip install usearch ``` - [npm](https://www.npmjs.com/package/usearch) (📥 9.2K / month · 📦 15 · ⏱️ 23.01.2025): ``` npm install usearch ``` - [Docker Hub](https://hub.docker.com/r/unum/usearch) (📥 200 · ⭐ 1 · ⏱️ 16.04.2025): ``` docker pull unum/usearch ``` </details> <details><summary><b><a href="https://github.com/lmcinnes/pynndescent">PyNNDescent</a></b> (🥉28 · ⭐ 920) - 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) (👨‍💻 30 · 🔀 110 · 📦 11K · 📋 140 - 52% open · ⏱️ 10.11.2024): ``` git clone https://github.com/lmcinnes/pynndescent ``` - [PyPi](https://pypi.org/project/pynndescent) (📥 1.6M / month · 📦 160 · ⏱️ 17.06.2024): ``` pip install pynndescent ``` - [Conda](https://anaconda.org/conda-forge/pynndescent) (📥 2.3M · ⏱️ 22.04.2025): ``` conda install -c conda-forge pynndescent ``` </details> <details><summary><b><a href="https://github.com/yahoojapan/NGT">NGT</a></b> (🥉24 · ⭐ 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) (👨‍💻 18 · 🔀 120 · 📋 140 - 15% open · ⏱️ 24.04.2025): ``` git clone https://github.com/yahoojapan/NGT ``` - [PyPi](https://pypi.org/project/ngt) (📥 3.1K / month · 📦 12 · ⏱️ 26.02.2025): ``` pip install ngt ``` </details> <details><summary>Show 4 hidden projects...</summary> - <b><a href="https://github.com/pixelogik/NearPy">NearPy</a></b> (🥉21 · ⭐ 770 · 💀) - 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/plasticityai/magnitude">Magnitude</a></b> (🥉20 · ⭐ 1.6K · 💀) - A fast, efficient universal vector embedding utility package. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/kakao/n2">N2</a></b> (🥉20 · ⭐ 580 · 💀) - 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> (🥉11 · ⭐ 920 · 💀) - 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> (🥇41 · ⭐ 9K) - 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) (👨‍💻 510 · 🔀 2.1K · 📥 2K · 📦 6.6K · 📋 3.5K - 10% open · ⏱️ 20.04.2025): ``` git clone https://github.com/pymc-devs/pymc ``` - [PyPi](https://pypi.org/project/pymc3) (📥 310K / month · 📦 190 · ⏱️ 31.05.2024): ``` pip install pymc3 ``` - [Conda](https://anaconda.org/conda-forge/pymc3) (📥 660K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pymc3 ``` </details> <details><summary><b><a href="https://github.com/tensorflow/probability">tensorflow-probability</a></b> (🥇37 · ⭐ 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) (👨‍💻 500 · 🔀 1.1K · 📦 3 · 📋 1.5K - 48% open · ⏱️ 15.04.2025): ``` git clone https://github.com/tensorflow/probability ``` - [PyPi](https://pypi.org/project/tensorflow-probability) (📥 1.6M / month · 📦 620 · ⏱️ 08.11.2024): ``` pip install tensorflow-probability ``` - [Conda](https://anaconda.org/conda-forge/tensorflow-probability) (📥 170K · ⏱️ 22.04.2025): ``` conda install -c conda-forge tensorflow-probability ``` </details> <details><summary><b><a href="https://github.com/pgmpy/pgmpy">pgmpy</a></b> (🥇34 · ⭐ 2.9K) - 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) (👨‍💻 140 · 🔀 730 · 📥 600 · 📦 1.6K · 📋 1K - 30% open · ⏱️ 22.04.2025): ``` git clone https://github.com/pgmpy/pgmpy ``` - [PyPi](https://pypi.org/project/pgmpy) (📥 150K / month · 📦 72 · ⏱️ 31.03.2025): ``` pip install pgmpy ``` </details> <details><summary><b><a href="https://github.com/pyro-ppl/pyro">Pyro</a></b> (🥈33 · ⭐ 8.7K) - 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) (👨‍💻 160 · 🔀 990 · 📋 1.1K - 23% open · ⏱️ 14.04.2025): ``` git clone https://github.com/pyro-ppl/pyro ``` - [PyPi](https://pypi.org/project/pyro-ppl) (📥 390K / month · 📦 190 · ⏱️ 02.06.2024): ``` pip install pyro-ppl ``` - [Conda](https://anaconda.org/conda-forge/pyro-ppl) (📥 230K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pyro-ppl ``` </details> <details><summary><b><a href="https://github.com/pydata/patsy">patsy</a></b> (🥈33 · ⭐ 970) - 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) (👨‍💻 22 · 🔀 100 · 📦 120K · 📋 160 - 46% open · ⏱️ 24.02.2025): ``` git clone https://github.com/pydata/patsy ``` - [PyPi](https://pypi.org/project/patsy) (📥 16M / month · 📦 530 · ⏱️ 12.11.2024): ``` pip install patsy ``` - [Conda](https://anaconda.org/conda-forge/patsy) (📥 15M · ⏱️ 22.04.2025): ``` conda install -c conda-forge patsy ``` </details> <details><summary><b><a href="https://github.com/twopirllc/pandas-ta">pandas-ta</a></b> (🥈32 · ⭐ 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) (👨‍💻 45 · 🔀 1.2K · 📦 5.3K · 📋 720 - 14% open · ⏱️ 24.06.2024): ``` git clone https://github.com/twopirllc/pandas-ta ``` - [PyPi](https://pypi.org/project/pandas-ta) (📥 180K / month · 📦 140 · ⏱️ 28.07.2021): ``` pip install pandas-ta ``` - [Conda](https://anaconda.org/conda-forge/pandas-ta) (📥 26K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pandas-ta ``` </details> <details><summary><b><a href="https://github.com/cornellius-gp/gpytorch">GPyTorch</a></b> (🥈31 · ⭐ 3.7K) - 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) (👨‍💻 140 · 🔀 560 · 📦 2.8K · 📋 1.4K - 27% open · ⏱️ 07.02.2025): ``` git clone https://github.com/cornellius-gp/gpytorch ``` - [PyPi](https://pypi.org/project/gpytorch) (📥 290K / month · 📦 190 · ⏱️ 29.01.2025): ``` pip install gpytorch ``` - [Conda](https://anaconda.org/conda-forge/gpytorch) (📥 200K · ⏱️ 22.04.2025): ``` conda install -c conda-forge gpytorch ``` </details> <details><summary><b><a href="https://github.com/hmmlearn/hmmlearn">hmmlearn</a></b> (🥈30 · ⭐ 3.2K) - 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) (👨‍💻 49 · 🔀 740 · 📦 3.4K · 📋 450 - 15% open · ⏱️ 31.10.2024): ``` git clone https://github.com/hmmlearn/hmmlearn ``` - [PyPi](https://pypi.org/project/hmmlearn) (📥 160K / month · 📦 92 · ⏱️ 31.10.2024): ``` pip install hmmlearn ``` - [Conda](https://anaconda.org/conda-forge/hmmlearn) (📥 360K · ⏱️ 22.04.2025): ``` conda install -c conda-forge hmmlearn ``` </details> <details><summary><b><a href="https://github.com/dfm/emcee">emcee</a></b> (🥈30 · ⭐ 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) (👨‍💻 75 · 🔀 430 · 📦 2.9K · 📋 300 - 19% open · ⏱️ 16.03.2025): ``` git clone https://github.com/dfm/emcee ``` - [PyPi](https://pypi.org/project/emcee) (📥 150K / month · 📦 440 · ⏱️ 19.04.2024): ``` pip install emcee ``` - [Conda](https://anaconda.org/conda-forge/emcee) (📥 400K · ⏱️ 22.04.2025): ``` conda install -c conda-forge emcee ``` </details> <details><summary><b><a href="https://github.com/GPflow/GPflow">GPflow</a></b> (🥉29 · ⭐ 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) (👨‍💻 84 · 🔀 440 · 📦 750 · 📋 840 - 18% open · ⏱️ 29.01.2025): ``` git clone https://github.com/GPflow/GPflow ``` - [PyPi](https://pypi.org/project/gpflow) (📥 70K / month · 📦 35 · ⏱️ 17.06.2024): ``` pip install gpflow ``` - [Conda](https://anaconda.org/conda-forge/gpflow) (📥 43K · ⏱️ 22.04.2025): ``` conda install -c conda-forge gpflow ``` </details> <details><summary><b><a href="https://github.com/bambinos/bambi">bambi</a></b> (🥉28 · ⭐ 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) (👨‍💻 47 · 🔀 130 · 📦 200 · 📋 440 - 20% open · ⏱️ 16.04.2025): ``` git clone https://github.com/bambinos/bambi ``` - [PyPi](https://pypi.org/project/bambi) (📥 38K / month · 📦 14 · ⏱️ 21.12.2024): ``` pip install bambi ``` - [Conda](https://anaconda.org/conda-forge/bambi) (📥 47K · ⏱️ 22.04.2025): ``` conda install -c conda-forge bambi ``` </details> <details><summary><b><a href="https://github.com/SALib/SALib">SALib</a></b> (🥉28 · ⭐ 920) - 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) (👨‍💻 51 · 🔀 240 · 📦 1.5K · 📋 340 - 15% open · ⏱️ 18.04.2025): ``` git clone https://github.com/SALib/SALib ``` - [PyPi](https://pypi.org/project/salib) (📥 260K / month · 📦 130 · ⏱️ 19.08.2024): ``` pip install salib ``` - [Conda](https://anaconda.org/conda-forge/salib) (📥 210K · ⏱️ 22.04.2025): ``` conda install -c conda-forge salib ``` </details> <details><summary><b><a href="https://github.com/stan-dev/pystan">PyStan</a></b> (🥉28 · ⭐ 350 · 💤) - PyStan, a Python interface to Stan, a platform for statistical.. <code><a href="http://bit.ly/3hkKRql">ISC</a></code></summary> - [GitHub](https://github.com/stan-dev/pystan) (👨‍💻 14 · 🔀 60 · 📦 10K · 📋 200 - 6% open · ⏱️ 03.07.2024): ``` git clone https://github.com/stan-dev/pystan ``` - [PyPi](https://pypi.org/project/pystan) (📥 860K / month · 📦 160 · ⏱️ 03.07.2024): ``` pip install pystan ``` - [Conda](https://anaconda.org/conda-forge/pystan) (📥 3M · ⏱️ 22.04.2025): ``` conda install -c conda-forge pystan ``` </details> <details><summary><b><a href="https://github.com/jmschrei/pomegranate">pomegranate</a></b> (🥉27 · ⭐ 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) (👨‍💻 75 · 🔀 590 · 📋 790 - 3% open · ⏱️ 07.02.2025): ``` git clone https://github.com/jmschrei/pomegranate ``` - [PyPi](https://pypi.org/project/pomegranate) (📥 29K / month · 📦 67 · ⏱️ 07.02.2025): ``` pip install pomegranate ``` - [Conda](https://anaconda.org/conda-forge/pomegranate) (📥 200K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pomegranate ``` </details> <details><summary><b><a href="https://github.com/maximtrp/scikit-posthocs">scikit-posthocs</a></b> (🥉27 · ⭐ 360) - 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) (👨‍💻 16 · 🔀 40 · 📥 66 · 📦 1.1K · 📋 72 - 6% open · ⏱️ 16.04.2025): ``` git clone https://github.com/maximtrp/scikit-posthocs ``` - [PyPi](https://pypi.org/project/scikit-posthocs) (📥 88K / month · 📦 73 · ⏱️ 29.03.2025): ``` pip install scikit-posthocs ``` - [Conda](https://anaconda.org/conda-forge/scikit-posthocs) (📥 1M · ⏱️ 22.04.2025): ``` conda install -c conda-forge scikit-posthocs ``` </details> <details><summary><b><a href="https://github.com/uber/orbit">Orbit</a></b> (🥉24 · ⭐ 2K · 💤) - A Python package for Bayesian forecasting with object-oriented.. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/uber/orbit) (👨‍💻 20 · 🔀 140 · 📦 68 · 📋 400 - 12% open · ⏱️ 10.07.2024): ``` git clone https://github.com/uber/orbit ``` - [PyPi](https://pypi.org/project/orbit-ml) (📥 15K / month · 📦 1 · ⏱️ 01.04.2024): ``` pip install orbit-ml ``` </details> <details><summary><b><a href="https://github.com/ENSTA-U2IS-AI/torch-uncertainty">TorchUncertainty</a></b> (🥉23 · ⭐ 380) - 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) (👨‍💻 12 · 🔀 28 · 📋 50 - 28% open · ⏱️ 20.03.2025): ``` git clone https://github.com/ENSTA-U2IS-AI/torch-uncertainty ``` - [PyPi](https://pypi.org/project/torch-uncertainty) (📥 1.4K / month · 📦 4 · ⏱️ 20.03.2025): ``` pip install torch-uncertainty ``` </details> <details><summary><b><a href="https://github.com/baal-org/baal">Baal</a></b> (🥉22 · ⭐ 900 · 💤) - 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) (👨‍💻 23 · 🔀 87 · 📦 66 · 📋 110 - 17% open · ⏱️ 27.06.2024): ``` git clone https://github.com/baal-org/baal ``` - [PyPi](https://pypi.org/project/baal) (📥 1.8K / month · 📦 2 · ⏱️ 11.06.2024): ``` pip install baal ``` - [Conda](https://anaconda.org/conda-forge/baal) (📥 12K · ⏱️ 22.04.2025): ``` conda install -c conda-forge baal ``` </details> <details><summary><b><a href="https://github.com/mattjj/pyhsmm">pyhsmm</a></b> (🥉20 · ⭐ 560) - Bayesian inference in HSMMs and HMMs. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/mattjj/pyhsmm) (👨‍💻 14 · 🔀 170 · 📦 34 · 📋 100 - 39% open · ⏱️ 25.01.2025): ``` git clone https://github.com/mattjj/pyhsmm ``` - [PyPi](https://pypi.org/project/pyhsmm) (📥 320 / month · 📦 1 · ⏱️ 10.05.2017): ``` pip install pyhsmm ``` </details> <details><summary>Show 5 hidden projects...</summary> - <b><a href="https://github.com/rlabbe/filterpy">filterpy</a></b> (🥈32 · ⭐ 3.5K · 💀) - 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> (🥈30 · ⭐ 1.7K) - Statistical package in Python based on Pandas. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/blei-lab/edward">Edward</a></b> (🥉28 · ⭐ 4.8K · 💀) - 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/pyro-ppl/funsor">Funsor</a></b> (🥉20 · ⭐ 240 · 💀) - 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> (🥉15 · ⭐ 2.2K · 💀) - 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> (🥇32 · ⭐ 5.2K) - 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) (👨‍💻 140 · 🔀 1.2K · 📦 710 · 📋 900 - 2% open · ⏱️ 28.02.2025): ``` git clone https://github.com/Trusted-AI/adversarial-robustness-toolbox ``` - [PyPi](https://pypi.org/project/adversarial-robustness-toolbox) (📥 29K / month · 📦 20 · ⏱️ 22.01.2025): ``` pip install adversarial-robustness-toolbox ``` - [Conda](https://anaconda.org/conda-forge/adversarial-robustness-toolbox) (📥 70K · ⏱️ 22.04.2025): ``` conda install -c conda-forge adversarial-robustness-toolbox ``` </details> <details><summary><b><a href="https://github.com/QData/TextAttack">TextAttack</a></b> (🥈29 · ⭐ 3.1K · 💤) - 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) (👨‍💻 66 · 🔀 400 · 📦 380 · 📋 290 - 23% open · ⏱️ 25.07.2024): ``` git clone https://github.com/QData/TextAttack ``` - [PyPi](https://pypi.org/project/textattack) (📥 8.1K / month · 📦 11 · ⏱️ 11.03.2024): ``` pip install textattack ``` - [Conda](https://anaconda.org/conda-forge/textattack) (📥 10K · ⏱️ 22.04.2025): ``` conda install -c conda-forge textattack ``` </details> <details><summary>Show 7 hidden projects...</summary> - <b><a href="https://github.com/cleverhans-lab/cleverhans">CleverHans</a></b> (🥈30 · ⭐ 6.3K · 💀) - 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/bethgelab/foolbox">Foolbox</a></b> (🥈28 · ⭐ 2.9K · 💀) - A Python toolbox to create adversarial examples that fool neural.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/BorealisAI/advertorch">advertorch</a></b> (🥉24 · ⭐ 1.3K · 💀) - A Toolbox for Adversarial Robustness Research. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-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/MadryLab/robustness">robustness</a></b> (🥉21 · ⭐ 940 · 💀) - 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/advboxes/AdvBox">AdvBox</a></b> (🥉19 · ⭐ 1.4K · 💀) - 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/textflint/textflint">textflint</a></b> (🥉17 · ⭐ 640 · 💀) - Unified Multilingual Robustness Evaluation Toolkit for.. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-3.0</a></code> - <b><a href="https://github.com/airbnb/artificial-adversary">Adversary</a></b> (🥉16 · ⭐ 400 · 💀) - 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/rapidsai/cudf">cuDF</a></b> (🥇35 · ⭐ 8.9K) - cuDF - GPU DataFrame Library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/rapidsai/cudf) (👨‍💻 300 · 🔀 940 · 📦 62 · 📋 6.9K - 15% open · ⏱️ 24.04.2025): ``` git clone https://github.com/rapidsai/cudf ``` - [PyPi](https://pypi.org/project/cudf) (📥 3.7K / month · 📦 22 · ⏱️ 01.06.2020): ``` pip install cudf ``` </details> <details><summary><b><a href="https://github.com/huggingface/optimum">optimum</a></b> (🥇35 · ⭐ 2.9K) - 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) (👨‍💻 140 · 🔀 520 · 📦 5.3K · 📋 890 - 44% open · ⏱️ 24.04.2025): ``` git clone https://github.com/huggingface/optimum ``` - [PyPi](https://pypi.org/project/optimum) (📥 1.3M / month · 📦 200 · ⏱️ 30.01.2025): ``` pip install optimum ``` - [Conda](https://anaconda.org/conda-forge/optimum) (📥 37K · ⏱️ 22.04.2025): ``` conda install -c conda-forge optimum ``` </details> <details><summary><b><a href="https://github.com/NVIDIA/apex">Apex</a></b> (🥈32 · ⭐ 8.6K) - 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) (👨‍💻 130 · 🔀 1.4K · 📦 3.1K · 📋 1.3K - 58% open · ⏱️ 11.04.2025): ``` git clone https://github.com/NVIDIA/apex ``` - [Conda](https://anaconda.org/conda-forge/nvidia-apex) (📥 480K · ⏱️ 22.04.2025): ``` conda install -c conda-forge nvidia-apex ``` </details> <details><summary><b><a href="https://github.com/rapidsai/cuml">cuML</a></b> (🥈32 · ⭐ 4.7K) - cuML - RAPIDS Machine Learning Library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/rapidsai/cuml) (👨‍💻 180 · 🔀 570 · 📋 2.7K - 36% open · ⏱️ 22.04.2025): ``` git clone https://github.com/rapidsai/cuml ``` - [PyPi](https://pypi.org/project/cuml) (📥 4.6K / month · 📦 14 · ⏱️ 01.06.2020): ``` pip install cuml ``` </details> <details><summary><b><a href="https://github.com/inducer/pycuda">PyCUDA</a></b> (🥈31 · ⭐ 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) (👨‍💻 82 · 🔀 290 · 📦 3.7K · 📋 280 - 30% open · ⏱️ 07.02.2025): ``` git clone https://github.com/inducer/pycuda ``` - [PyPi](https://pypi.org/project/pycuda) (📥 78K / month · 📦 170 · ⏱️ 07.02.2025): ``` pip install pycuda ``` - [Conda](https://anaconda.org/conda-forge/pycuda) (📥 950K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pycuda ``` </details> <details><summary><b><a href="https://github.com/wookayin/gpustat">gpustat</a></b> (🥈29 · ⭐ 4.2K) - 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) (👨‍💻 17 · 🔀 280 · 📦 7.2K · 📋 130 - 22% open · ⏱️ 13.04.2025): ``` git clone https://github.com/wookayin/gpustat ``` - [PyPi](https://pypi.org/project/gpustat) (📥 690K / month · 📦 150 · ⏱️ 22.08.2023): ``` pip install gpustat ``` - [Conda](https://anaconda.org/conda-forge/gpustat) (📥 310K · ⏱️ 22.04.2025): ``` conda install -c conda-forge gpustat ``` </details> <details><summary><b><a href="https://github.com/arrayfire/arrayfire">ArrayFire</a></b> (🥈28 · ⭐ 4.7K) - ArrayFire: a general purpose GPU library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/arrayfire/arrayfire) (👨‍💻 97 · 🔀 540 · 📥 8.3K · 📋 1.8K - 19% open · ⏱️ 04.04.2025): ``` git clone https://github.com/arrayfire/arrayfire ``` - [PyPi](https://pypi.org/project/arrayfire) (📥 3.3K / month · 📦 10 · ⏱️ 22.02.2022): ``` pip install arrayfire ``` </details> <details><summary><b><a href="https://github.com/cupy/cupy">CuPy</a></b> (🥈27 · ⭐ 10K) - NumPy & SciPy for GPU. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/cupy/cupy) (👨‍💻 340 · 🔀 900): ``` git clone https://github.com/cupy/cupy ``` - [PyPi](https://pypi.org/project/cupy) (📥 36K / month · 📦 350 · ⏱️ 04.04.2025): ``` pip install cupy ``` - [Conda](https://anaconda.org/conda-forge/cupy) (📥 6.2M · ⏱️ 22.04.2025): ``` conda install -c conda-forge cupy ``` - [Docker Hub](https://hub.docker.com/r/cupy/cupy) (📥 81K · ⭐ 13 · ⏱️ 04.04.2025): ``` docker pull cupy/cupy ``` </details> <details><summary><b><a href="https://github.com/rapidsai/cugraph">cuGraph</a></b> (🥈27 · ⭐ 2K) - cuGraph - RAPIDS Graph Analytics Library. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code></summary> - [GitHub](https://github.com/rapidsai/cugraph) (👨‍💻 120 · 🔀 320 · 📋 1.8K - 9% open · ⏱️ 23.04.2025): ``` git clone https://github.com/rapidsai/cugraph ``` - [PyPi](https://pypi.org/project/cugraph) (📥 380 / month · 📦 4 · ⏱️ 01.06.2020): ``` pip install cugraph ``` - [Conda](https://anaconda.org/conda-forge/libcugraph) (📥 29K · ⏱️ 22.04.2025): ``` conda install -c conda-forge libcugraph ``` </details> <details><summary><b><a href="https://github.com/NVIDIA/DALI">DALI</a></b> (🥉25 · ⭐ 5.4K) - 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) (👨‍💻 96 · 🔀 630 · 📋 1.7K - 14% open · ⏱️ 24.04.2025): ``` git clone https://github.com/NVIDIA/DALI ``` </details> <details><summary><b><a href="https://github.com/KomputeProject/kompute">Vulkan Kompute</a></b> (🥉23 · ⭐ 2.2K) - 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) (👨‍💻 32 · 🔀 160 · 📥 640 · 📋 220 - 32% open · ⏱️ 19.03.2025): ``` git clone https://github.com/KomputeProject/kompute ``` - [PyPi](https://pypi.org/project/kp) (📥 560 / month · ⏱️ 20.01.2024): ``` pip install kp ``` </details> <details><summary><b><a href="https://github.com/NVIDIA-Merlin/Merlin">Merlin</a></b> (🥉20 · ⭐ 820 · 💤) - 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) (👨‍💻 32 · 🔀 120 · 📋 460 - 46% open · ⏱️ 22.07.2024): ``` git clone https://github.com/NVIDIA-Merlin/Merlin ``` - [PyPi](https://pypi.org/project/merlin-core) (📥 25K / month · 📦 1 · ⏱️ 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> (🥉25 · ⭐ 1.2K · 💀) - 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> (🥉24 · ⭐ 990 · 💀) - 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> (🥉23 · ⭐ 250 · 💀) - 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> (🥉21 · ⭐ 2K · 💀) - 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> (🥉19 · ⭐ 140 · 💤) - 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> (🥉16 · ⭐ 720 · 💀) - 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> (🥉16 · ⭐ 680 · 💀) - 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> (🥉16 · ⭐ 220 · 💀) - 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> (🥇38 · ⭐ 4.4K · 📉) - 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) (👨‍💻 490 · 🔀 1.6K · 📦 23K · 📋 1.5K - 47% open · ⏱️ 15.04.2025): ``` git clone https://github.com/tensorflow/datasets ``` - [PyPi](https://pypi.org/project/tensorflow-datasets) (📥 1.6M / month · 📦 340 · ⏱️ 12.03.2025): ``` pip install tensorflow-datasets ``` - [Conda](https://anaconda.org/conda-forge/tensorflow-datasets) (📥 46K · ⏱️ 22.04.2025): ``` conda install -c conda-forge tensorflow-datasets ``` </details> <details><summary><b><a href="https://github.com/tensorflow/hub">tensorflow-hub</a></b> (🥇33 · ⭐ 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) (👨‍💻 110 · 🔀 1.7K · 📋 710 - 1% open · ⏱️ 17.01.2025): ``` git clone https://github.com/tensorflow/hub ``` - [PyPi](https://pypi.org/project/tensorflow-hub) (📥 2M / month · 📦 300 · ⏱️ 30.01.2024): ``` pip install tensorflow-hub ``` - [Conda](https://anaconda.org/conda-forge/tensorflow-hub) (📥 120K · ⏱️ 22.04.2025): ``` conda install -c conda-forge tensorflow-hub ``` </details> <details><summary><b><a href="https://github.com/tensorflow/tfx">TFX</a></b> (🥈32 · ⭐ 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) (👨‍💻 190 · 🔀 710 · 📦 1.8K · 📋 1.1K - 22% open · ⏱️ 26.03.2025): ``` git clone https://github.com/tensorflow/tfx ``` - [PyPi](https://pypi.org/project/tfx) (📥 44K / month · 📦 17 · ⏱️ 11.12.2024): ``` pip install tfx ``` </details> <details><summary><b><a href="https://github.com/tensorflow/addons">TF Addons</a></b> (🥈32 · ⭐ 1.7K · 💤) - 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) (👨‍💻 210 · 🔀 610 · 📋 990 - 9% open · ⏱️ 15.04.2024): ``` git clone https://github.com/tensorflow/addons ``` - [PyPi](https://pypi.org/project/tensorflow-addons) (📥 1.1M / month · 📦 370 · ⏱️ 28.11.2023): ``` pip install tensorflow-addons ``` </details> <details><summary><b><a href="https://github.com/tensorflow/io">TensorFlow I/O</a></b> (🥈30 · ⭐ 720) - 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) (👨‍💻 120 · 🔀 290 · 📋 660 - 44% open · ⏱️ 10.04.2025): ``` git clone https://github.com/tensorflow/io ``` - [PyPi](https://pypi.org/project/tensorflow-io) (📥 770K / month · 📦 61 · ⏱️ 01.07.2024): ``` pip install tensorflow-io ``` </details> <details><summary><b><a href="https://github.com/tensorflow/model-optimization">TF Model Optimization</a></b> (🥉28 · ⭐ 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) (👨‍💻 87 · 🔀 320 · 📋 400 - 57% open · ⏱️ 10.02.2025): ``` git clone https://github.com/tensorflow/model-optimization ``` - [PyPi](https://pypi.org/project/tensorflow-model-optimization) (📥 250K / month · 📦 45 · ⏱️ 08.02.2024): ``` pip install tensorflow-model-optimization ``` </details> <details><summary><b><a href="https://github.com/tensorflow/transform">TensorFlow Transform</a></b> (🥉25 · ⭐ 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) (👨‍💻 29 · 🔀 220 · 📋 220 - 17% open · ⏱️ 17.03.2025): ``` git clone https://github.com/tensorflow/transform ``` - [PyPi](https://pypi.org/project/tensorflow-transform) (📥 240K / month · 📦 18 · ⏱️ 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> (🥉23 · ⭐ 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) (👨‍💻 39 · 🔀 190 · 📦 510 · 📋 69 - 1% open · ⏱️ 29.01.2025): ``` git clone https://github.com/tensorflow/neural-structured-learning ``` - [PyPi](https://pypi.org/project/neural-structured-learning) (📥 5.5K / month · 📦 3 · ⏱️ 29.07.2022): ``` pip install neural-structured-learning ``` </details> <details><summary><b><a href="https://github.com/tensorflow/compression">TF Compression</a></b> (🥉20 · ⭐ 880) - 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) (👨‍💻 24 · 🔀 250 · 📋 100 - 10% open · ⏱️ 15.04.2025): ``` git clone https://github.com/tensorflow/compression ``` - [PyPi](https://pypi.org/project/tensorflow-compression) (📥 3.7K / month · 📦 2 · ⏱️ 02.02.2024): ``` pip install tensorflow-compression ``` </details> <details><summary><b><a href="https://github.com/tensorflow/cloud">TensorFlow Cloud</a></b> (🥉20 · ⭐ 380) - 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) (👨‍💻 28 · 🔀 90 · 📋 100 - 73% open · ⏱️ 29.01.2025): ``` git clone https://github.com/tensorflow/cloud ``` - [PyPi](https://pypi.org/project/tensorflow-cloud) (📥 37K / month · 📦 7 · ⏱️ 17.06.2021): ``` pip install tensorflow-cloud ``` </details> <details><summary>Show 6 hidden projects...</summary> - <b><a href="https://github.com/tensorflow/tensor2tensor">tensor2tensor</a></b> (🥇33 · ⭐ 16K · 💀) - 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> (🥈29 · ⭐ 1K · 💀) - 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> (🥉27 · ⭐ 2.1K · 💀) - 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/PAIR-code/saliency">Saliency</a></b> (🥉22 · ⭐ 970 · 💀) - 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> - <b><a href="https://github.com/taehoonlee/tensornets">TensorNets</a></b> (🥉21 · ⭐ 1K · 💀) - 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> (🥉19 · ⭐ 780 · 💀) - 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> (🥇31 · ⭐ 2.3K) - 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) (👨‍💻 65 · 🔀 160 · 📦 1.2K · 📋 540 - 34% open · ⏱️ 21.04.2025): ``` git clone https://github.com/patrick-kidger/equinox ``` - [PyPi](https://pypi.org/project/equinox) (📥 290K / month · 📦 230 · ⏱️ 27.03.2025): ``` pip install equinox ``` </details> <details><summary><b><a href="https://github.com/google/evojax">evojax</a></b> (🥉20 · ⭐ 900 · 💤) - 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) (👨‍💻 14 · 🔀 100 · 📦 28 · 📋 37 - 54% open · ⏱️ 27.06.2024): ``` git clone https://github.com/google/evojax ``` - [PyPi](https://pypi.org/project/evojax) (📥 1.3K / month · 📦 6 · ⏱️ 18.06.2024): ``` pip install evojax ``` - [Conda](https://anaconda.org/conda-forge/evojax) (📥 37K · ⏱️ 22.04.2025): ``` 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> (🥉11 · ⭐ 120 · 💤) - A JAX-based research framework for writing differentiable.. <code><a href="http://bit.ly/37RvQcA">❗️LGPL-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> (🥇35 · ⭐ 5K) - A library of extension and helper modules for Pythons data analysis.. <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) (👨‍💻 110 · 🔀 880 · 📦 19K · 📋 500 - 29% open · ⏱️ 26.01.2025): ``` git clone https://github.com/rasbt/mlxtend ``` - [PyPi](https://pypi.org/project/mlxtend) (📥 690K / month · 📦 200 · ⏱️ 26.01.2025): ``` pip install mlxtend ``` - [Conda](https://anaconda.org/conda-forge/mlxtend) (📥 350K · ⏱️ 22.04.2025): ``` conda install -c conda-forge mlxtend ``` </details> <details><summary><b><a href="https://github.com/uxlfoundation/scikit-learn-intelex">scikit-learn-intelex</a></b> (🥇35 · ⭐ 1.3K) - 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) (👨‍💻 85 · 🔀 180 · 📦 13K · 📋 250 - 20% open · ⏱️ 24.04.2025): ``` git clone https://github.com/intel/scikit-learn-intelex ``` - [PyPi](https://pypi.org/project/scikit-learn-intelex) (📥 76K / month · 📦 65 · ⏱️ 22.04.2025): ``` pip install scikit-learn-intelex ``` - [Conda](https://anaconda.org/conda-forge/scikit-learn-intelex) (📥 510K · ⏱️ 22.04.2025): ``` 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> (🥈33 · ⭐ 7K) - 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) (👨‍💻 87 · 🔀 1.3K · 📋 620 - 7% open · ⏱️ 01.04.2025): ``` git clone https://github.com/scikit-learn-contrib/imbalanced-learn ``` - [PyPi](https://pypi.org/project/imbalanced-learn) (📥 14M / month · 📦 480 · ⏱️ 20.12.2024): ``` pip install imbalanced-learn ``` - [Conda](https://anaconda.org/conda-forge/imbalanced-learn) (📥 690K · ⏱️ 22.04.2025): ``` 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> (🥈32 · ⭐ 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) (👨‍💻 71 · 🔀 400 · 📦 3.4K · 📋 300 - 14% open · ⏱️ 24.03.2025): ``` git clone https://github.com/scikit-learn-contrib/category_encoders ``` - [PyPi](https://pypi.org/project/category_encoders) (📥 2M / month · 📦 310 · ⏱️ 15.03.2025): ``` pip install category_encoders ``` - [Conda](https://anaconda.org/conda-forge/category_encoders) (📥 310K · ⏱️ 22.04.2025): ``` conda install -c conda-forge category_encoders ``` </details> <details><summary><b><a href="https://github.com/koaning/scikit-lego">scikit-lego</a></b> (🥈27 · ⭐ 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) (👨‍💻 68 · 🔀 120 · 📦 180 · 📋 340 - 11% open · ⏱️ 19.04.2025): ``` git clone https://github.com/koaning/scikit-lego ``` - [PyPi](https://pypi.org/project/scikit-lego) (📥 29K / month · 📦 13 · ⏱️ 17.12.2024): ``` pip install scikit-lego ``` - [Conda](https://anaconda.org/conda-forge/scikit-lego) (📥 66K · ⏱️ 22.04.2025): ``` conda install -c conda-forge scikit-lego ``` </details> <details><summary><b><a href="https://github.com/guofei9987/scikit-opt">scikit-opt</a></b> (🥉25 · ⭐ 5.5K · 💤) - 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) (👨‍💻 24 · 🔀 990 · 📦 260 · 📋 180 - 37% open · ⏱️ 23.06.2024): ``` git clone https://github.com/guofei9987/scikit-opt ``` - [PyPi](https://pypi.org/project/scikit-opt) (📥 5.7K / month · 📦 15 · ⏱️ 14.01.2022): ``` pip install scikit-opt ``` </details> <details><summary><b><a href="https://github.com/trent-b/iterative-stratification">iterative-stratification</a></b> (🥉21 · ⭐ 860) - 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) (👨‍💻 7 · 🔀 75 · 📦 580 · 📋 27 - 7% open · ⏱️ 12.10.2024): ``` git clone https://github.com/trent-b/iterative-stratification ``` - [PyPi](https://pypi.org/project/iterative-stratification) (📥 44K / month · 📦 15 · ⏱️ 12.10.2024): ``` pip install iterative-stratification ``` </details> <details><summary><b><a href="https://github.com/amueller/dabl">dabl</a></b> (🥉19 · ⭐ 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) (👨‍💻 24 · 🔀 100 · ⏱️ 07.08.2024): ``` git clone https://github.com/amueller/dabl ``` - [PyPi](https://pypi.org/project/dabl) (📥 4.2K / month · 📦 3 · ⏱️ 16.12.2024): ``` pip install dabl ``` </details> <details><summary><b><a href="https://github.com/scikit-tda/scikit-tda">scikit-tda</a></b> (🥉18 · ⭐ 540 · 💤) - 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) (👨‍💻 6 · 🔀 54 · 📦 83 · 📋 22 - 18% open · ⏱️ 19.07.2024): ``` git clone https://github.com/scikit-tda/scikit-tda ``` - [PyPi](https://pypi.org/project/scikit-tda) (📥 1.1K / month · ⏱️ 19.07.2024): ``` pip install scikit-tda ``` </details> <details><summary><b><a href="https://github.com/scikit-learn-contrib/DESlib">DESlib</a></b> (🥉18 · ⭐ 490 · 💤) - 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) (👨‍💻 17 · 🔀 100 · 📋 160 - 11% open · ⏱️ 15.04.2024): ``` git clone https://github.com/scikit-learn-contrib/DESlib ``` - [PyPi](https://pypi.org/project/deslib) (📥 3.8K / month · 📦 3 · ⏱️ 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> (🥈32 · ⭐ 1.2K) - Survival analysis built on top of scikit-learn. <code><a href="http://bit.ly/2M0xdwT">❗️GPL-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> (🥈27 · ⭐ 1.3K · 💀) - 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> (🥈27 · ⭐ 930 · 💀) - 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> (🥈27 · ⭐ 430 · 💀) - 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> (🥉24 · ⭐ 1.7K · 💀) - 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/scikit-learn-contrib/skope-rules">skope-rules</a></b> (🥉22 · ⭐ 630 · 💀) - machine learning with logical rules in Python. <code><a href="https://tldrlegal.com/search?q=BSD-1-Clause">❗️BSD-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> (🥉22 · ⭐ 220) - 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/yzhao062/combo">combo</a></b> (🥉21 · ⭐ 650 · 💀) - (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/skggm/skggm">skggm</a></b> (🥉18 · ⭐ 250 · 💀) - 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> (🥇42 · ⭐ 8.6K) - 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) (👨‍💻 340 · 🔀 1.1K · 📦 87K · 📋 1.8K - 6% open · ⏱️ 24.04.2025): ``` git clone https://github.com/huggingface/accelerate ``` - [PyPi](https://pypi.org/project/accelerate) (📥 11M / month · 📦 2K · ⏱️ 01.04.2025): ``` pip install accelerate ``` - [Conda](https://anaconda.org/conda-forge/accelerate) (📥 370K · ⏱️ 22.04.2025): ``` conda install -c conda-forge accelerate ``` </details> <details><summary><b><a href="https://github.com/tinygrad/tinygrad">tinygrad</a></b> (🥇35 · ⭐ 29K) - 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) (👨‍💻 390 · 🔀 3.3K · 📦 200 · 📋 900 - 14% open · ⏱️ 24.04.2025): ``` git clone https://github.com/geohot/tinygrad ``` </details> <details><summary><b><a href="https://github.com/KevinMusgrave/pytorch-metric-learning">PML</a></b> (🥇33 · ⭐ 6.1K) - 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) (👨‍💻 46 · 🔀 660 · 📦 2.6K · 📋 530 - 14% open · ⏱️ 11.12.2024): ``` git clone https://github.com/KevinMusgrave/pytorch-metric-learning ``` - [PyPi](https://pypi.org/project/pytorch-metric-learning) (📥 770K / month · 📦 55 · ⏱️ 11.12.2024): ``` pip install pytorch-metric-learning ``` - [Conda](https://anaconda.org/metric-learning/pytorch-metric-learning) (📥 13K · ⏱️ 25.03.2025): ``` conda install -c metric-learning pytorch-metric-learning ``` </details> <details><summary><b><a href="https://github.com/rtqichen/torchdiffeq">torchdiffeq</a></b> (🥇33 · ⭐ 5.9K) - 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) (👨‍💻 22 · 🔀 930 · 📦 5K · 📋 220 - 33% open · ⏱️ 04.04.2025): ``` git clone https://github.com/rtqichen/torchdiffeq ``` - [PyPi](https://pypi.org/project/torchdiffeq) (📥 1.1M / month · 📦 120 · ⏱️ 21.11.2024): ``` pip install torchdiffeq ``` - [Conda](https://anaconda.org/conda-forge/torchdiffeq) (📥 21K · ⏱️ 22.04.2025): ``` conda install -c conda-forge torchdiffeq ``` </details> <details><summary><b><a href="https://github.com/google-research/torchsde">torchsde</a></b> (🥈30 · ⭐ 1.6K) - 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></summary> - [GitHub](https://github.com/google-research/torchsde) (👨‍💻 9 · 🔀 200 · 📦 5K · 📋 82 - 35% open · ⏱️ 30.12.2024): ``` git clone https://github.com/google-research/torchsde ``` - [PyPi](https://pypi.org/project/torchsde) (📥 2.6M / month · 📦 37 · ⏱️ 26.09.2023): ``` pip install torchsde ``` - [Conda](https://anaconda.org/conda-forge/torchsde) (📥 38K · ⏱️ 22.04.2025): ``` conda install -c conda-forge torchsde ``` </details> <details><summary><b><a href="https://github.com/rusty1s/pytorch_scatter">torch-scatter</a></b> (🥈27 · ⭐ 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) (👨‍💻 33 · 🔀 180 · 📋 410 - 6% open · ⏱️ 20.04.2025): ``` git clone https://github.com/rusty1s/pytorch_scatter ``` - [PyPi](https://pypi.org/project/torch-scatter) (📥 54K / month · 📦 150 · ⏱️ 06.10.2023): ``` pip install torch-scatter ``` - [Conda](https://anaconda.org/conda-forge/pytorch_scatter) (📥 820K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pytorch_scatter ``` </details> <details><summary><b><a href="https://github.com/BloodAxe/pytorch-toolbelt">Pytorch Toolbelt</a></b> (🥈26 · ⭐ 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) (👨‍💻 8 · 🔀 120 · 📥 140 · 📋 33 - 12% open · ⏱️ 01.03.2025): ``` git clone https://github.com/BloodAxe/pytorch-toolbelt ``` - [PyPi](https://pypi.org/project/pytorch_toolbelt) (📥 9.9K / month · 📦 12 · ⏱️ 21.11.2024): ``` pip install pytorch_toolbelt ``` </details> <details><summary><b><a href="https://github.com/rwightman/gen-efficientnet-pytorch">EfficientNets</a></b> (🥈25 · ⭐ 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) (👨‍💻 5 · 🔀 210 · 📦 290 · 📋 55 - 7% open · ⏱️ 13.06.2024): ``` git clone https://github.com/rwightman/gen-efficientnet-pytorch ``` - [PyPi](https://pypi.org/project/geffnet) (📥 190K / month · 📦 4 · ⏱️ 08.07.2021): ``` pip install geffnet ``` </details> <details><summary><b><a href="https://github.com/rusty1s/pytorch_sparse">PyTorch Sparse</a></b> (🥈25 · ⭐ 1.1K) - PyTorch Extension Library of Optimized Autograd Sparse.. <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) (👨‍💻 47 · 🔀 150 · 📋 290 - 10% open · ⏱️ 10.04.2025): ``` git clone https://github.com/rusty1s/pytorch_sparse ``` - [PyPi](https://pypi.org/project/torch-sparse) (📥 38K / month · 📦 120 · ⏱️ 06.10.2023): ``` pip install torch-sparse ``` - [Conda](https://anaconda.org/conda-forge/pytorch_sparse) (📥 770K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pytorch_sparse ``` </details> <details><summary><b><a href="https://github.com/facebookresearch/madgrad">madgrad</a></b> (🥉16 · ⭐ 800) - 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></summary> - [GitHub](https://github.com/facebookresearch/madgrad) (👨‍💻 3 · 🔀 57 · 📦 100 · ⏱️ 27.01.2025): ``` git clone https://github.com/facebookresearch/madgrad ``` - [PyPi](https://pypi.org/project/madgrad) (📥 3.9K / month · 📦 1 · ⏱️ 08.03.2022): ``` pip install madgrad ``` </details> <details><summary><b><a href="https://github.com/szagoruyko/pytorchviz">pytorchviz</a></b> (🥉14 · ⭐ 3.3K · 📉) - A small package to create visualizations of PyTorch execution.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/szagoruyko/pytorchviz) (👨‍💻 6 · 🔀 280 · 📋 72 - 47% open · ⏱️ 30.12.2024): ``` git clone https://github.com/szagoruyko/pytorchviz ``` </details> <details><summary>Show 21 hidden projects...</summary> - <b><a href="https://github.com/Cadene/pretrained-models.pytorch">pretrainedmodels</a></b> (🥈30 · ⭐ 9.1K · 💀) - 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/Lightning-Universe/lightning-flash">lightning-flash</a></b> (🥈29 · ⭐ 1.7K · 💀) - 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/lukemelas/EfficientNet-PyTorch">EfficientNet-PyTorch</a></b> (🥈27 · ⭐ 8.1K · 💀) - 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/jettify/pytorch-optimizer">pytorch-optimizer</a></b> (🥈27 · ⭐ 3.1K · 💀) - 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> (🥈26 · ⭐ 2.8K · 💀) - 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/tristandeleu/pytorch-meta">Torchmeta</a></b> (🥈25 · ⭐ 2K · 💀) - 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/sksq96/pytorch-summary">pytorch-summary</a></b> (🥉24 · ⭐ 4K · 💀) - 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/facebookresearch/higher">Higher</a></b> (🥉24 · ⭐ 1.6K · 💀) - 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/karpathy/micrograd">micrograd</a></b> (🥉22 · ⭐ 12K · 💀) - 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> (🥉22 · ⭐ 2.1K · 💀) - 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/Luolc/AdaBound">AdaBound</a></b> (🥉21 · ⭐ 2.9K · 💀) - 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> (🥉21 · ⭐ 2.2K · 💀) - 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/adobe/antialiased-cnns">Antialiased CNNs</a></b> (🥉21 · ⭐ 1.7K · 💀) - pip install antialiased-cnns to improve stability and.. <code><a href="https://tldrlegal.com/search?q=CC%20BY-NC-SA%204.0">❗️CC 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/lucidrains/performer-pytorch">Performer Pytorch</a></b> (🥉21 · ⭐ 1.1K · 💀) - 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/GRAAL-Research/poutyne">Poutyne</a></b> (🥉21 · ⭐ 570) - A simplified framework and utilities for PyTorch. <code><a href="http://bit.ly/37RvQcA">❗️LGPL-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> (🥉19 · ⭐ 1.5K · 💀) - 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/harvardnlp/pytorch-struct">Torch-Struct</a></b> (🥉19 · ⭐ 1.1K · 💀) - 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/parrt/tensor-sensor">Tensor Sensor</a></b> (🥉19 · ⭐ 800 · 💀) - 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/abhishekkrthakur/tez">Tez</a></b> (🥉18 · ⭐ 1.2K · 💀) - 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/achaiah/pywick">Pywick</a></b> (🥉17 · ⭐ 400 · 💀) - 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> (🥉15 · ⭐ 320 · 💀) - 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._ 🔗&nbsp;<b><a href="https://github.com/ml-tooling/best-of-python#database-clients">best-of-python - DB Clients</a></b> ( ⭐ 3.9K) - 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> (🥇50 · ⭐ 14K) - 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) (👨‍💻 1.8K · 🔀 5.3K · 📥 490K · 📦 1.3M · 📋 11K - 15% open · ⏱️ 23.04.2025): ``` git clone https://github.com/scipy/scipy ``` - [PyPi](https://pypi.org/project/scipy) (📥 140M / month · 📦 51K · ⏱️ 17.02.2025): ``` pip install scipy ``` - [Conda](https://anaconda.org/conda-forge/scipy) (📥 61M · ⏱️ 22.04.2025): ``` conda install -c conda-forge scipy ``` </details> <details><summary><b><a href="https://github.com/sympy/sympy">SymPy</a></b> (🥇49 · ⭐ 14K) - 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) (👨‍💻 1.4K · 🔀 4.7K · 📥 560K · 📦 250K · 📋 14K - 36% open · ⏱️ 22.04.2025): ``` git clone https://github.com/sympy/sympy ``` - [PyPi](https://pypi.org/project/sympy) (📥 49M / month · 📦 4.3K · ⏱️ 14.04.2025): ``` pip install sympy ``` - [Conda](https://anaconda.org/conda-forge/sympy) (📥 8.6M · ⏱️ 22.04.2025): ``` conda install -c conda-forge sympy ``` </details> <details><summary><b><a href="https://github.com/streamlit/streamlit">Streamlit</a></b> (🥇46 · ⭐ 39K) - 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) (👨‍💻 380 · 🔀 3.4K · 📦 860K · 📋 5.1K - 22% open · ⏱️ 24.04.2025): ``` git clone https://github.com/streamlit/streamlit ``` - [PyPi](https://pypi.org/project/streamlit) (📥 9.9M / month · 📦 3.5K · ⏱️ 01.04.2025): ``` pip install streamlit ``` </details> <details><summary><b><a href="https://github.com/gradio-app/gradio">Gradio</a></b> (🥇44 · ⭐ 38K) - 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) (👨‍💻 570 · 🔀 2.9K · 📦 70K · 📋 5.6K - 8% open · ⏱️ 23.04.2025): ``` git clone https://github.com/gradio-app/gradio ``` - [PyPi](https://pypi.org/project/gradio) (📥 9.4M / month · 📦 1.2K · ⏱️ 23.04.2025): ``` pip install gradio ``` </details> <details><summary><b><a href="https://github.com/carla-simulator/carla">carla</a></b> (🥇37 · ⭐ 12K) - 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) (👨‍💻 180 · 🔀 3.8K · 📦 1K · 📋 5.9K - 18% open · ⏱️ 24.04.2025): ``` git clone https://github.com/carla-simulator/carla ``` - [PyPi](https://pypi.org/project/carla) (📥 28K / month · 📦 11 · ⏱️ 14.11.2023): ``` pip install carla ``` </details> <details><summary><b><a href="https://github.com/PennyLaneAI/pennylane">PennyLane</a></b> (🥇37 · ⭐ 2.6K) - 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) (👨‍💻 200 · 🔀 650 · 📥 100 · 📦 1.5K · 📋 1.6K - 24% open · ⏱️ 24.04.2025): ``` git clone https://github.com/PennyLaneAI/PennyLane ``` - [PyPi](https://pypi.org/project/pennylane) (📥 94K / month · 📦 150 · ⏱️ 15.04.2025): ``` pip install pennylane ``` - [Conda](https://anaconda.org/conda-forge/pennylane) (📥 260K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pennylane ``` </details> <details><summary><b><a href="https://github.com/yzhao062/pyod">PyOD</a></b> (🥇36 · ⭐ 9.1K) - 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) (👨‍💻 63 · 🔀 1.4K · 📦 5.1K · 📋 380 - 60% open · ⏱️ 24.03.2025): ``` git clone https://github.com/yzhao062/pyod ``` - [PyPi](https://pypi.org/project/pyod) (📥 560K / month · 📦 130 · ⏱️ 24.03.2025): ``` pip install pyod ``` - [Conda](https://anaconda.org/conda-forge/pyod) (📥 150K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pyod ``` </details> <details><summary><b><a href="https://github.com/HIPS/autograd">Autograd</a></b> (🥇36 · ⭐ 7.2K · 📈) - Efficiently computes derivatives of NumPy code. <code><a href="http://bit.ly/34MBwT8">MIT</a></code></summary> - [GitHub](https://github.com/HIPS/autograd) (👨‍💻 61 · 🔀 910 · 📦 13K · 📋 430 - 42% open · ⏱️ 21.04.2025): ``` git clone https://github.com/HIPS/autograd ``` - [PyPi](https://pypi.org/project/autograd) (📥 4M / month · 📦 280 · ⏱️ 22.08.2024): ``` pip install autograd ``` - [Conda](https://anaconda.org/conda-forge/autograd) (📥 530K · ⏱️ 22.04.2025): ``` conda install -c conda-forge autograd ``` </details> <details><summary><b><a href="https://github.com/simonw/datasette">Datasette</a></b> (🥈35 · ⭐ 10K) - 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) (👨‍💻 82 · 🔀 730 · 📥 70 · 📦 1.5K · 📋 1.9K - 32% open · ⏱️ 22.04.2025): ``` git clone https://github.com/simonw/datasette ``` - [PyPi](https://pypi.org/project/datasette) (📥 200K / month · 📦 460 · ⏱️ 22.04.2025): ``` pip install datasette ``` - [Conda](https://anaconda.org/conda-forge/datasette) (📥 59K · ⏱️ 22.04.2025): ``` conda install -c conda-forge datasette ``` </details> <details><summary><b><a href="https://github.com/deepchem/deepchem">DeepChem</a></b> (🥈35 · ⭐ 5.9K) - 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) (👨‍💻 260 · 🔀 1.9K · 📦 570 · 📋 2K - 38% open · ⏱️ 21.04.2025): ``` git clone https://github.com/deepchem/deepchem ``` - [PyPi](https://pypi.org/project/deepchem) (📥 61K / month · 📦 17 · ⏱️ 22.04.2025): ``` pip install deepchem ``` - [Conda](https://anaconda.org/conda-forge/deepchem) (📥 110K · ⏱️ 22.04.2025): ``` conda install -c conda-forge deepchem ``` </details> <details><summary><b><a href="https://github.com/wireservice/agate">agate</a></b> (🥈35 · ⭐ 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) (👨‍💻 53 · 🔀 150 · 📦 4.8K · 📋 650 - 0% open · ⏱️ 27.02.2025): ``` git clone https://github.com/wireservice/agate ``` - [PyPi](https://pypi.org/project/agate) (📥 16M / month · 📦 54 · ⏱️ 29.01.2025): ``` pip install agate ``` - [Conda](https://anaconda.org/conda-forge/agate) (📥 310K · ⏱️ 22.04.2025): ``` conda install -c conda-forge agate ``` </details> <details><summary><b><a href="https://github.com/scikit-learn-contrib/hdbscan">hdbscan</a></b> (🥈33 · ⭐ 2.9K) - 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) (👨‍💻 96 · 🔀 500 · 📦 6K · 📋 530 - 67% open · ⏱️ 22.04.2025): ``` git clone https://github.com/scikit-learn-contrib/hdbscan ``` - [PyPi](https://pypi.org/project/hdbscan) (📥 710K / month · 📦 350 · ⏱️ 18.11.2024): ``` pip install hdbscan ``` - [Conda](https://anaconda.org/conda-forge/hdbscan) (📥 2.5M · ⏱️ 22.04.2025): ``` conda install -c conda-forge hdbscan ``` </details> <details><summary><b><a href="https://github.com/serge-sans-paille/pythran">Pythran</a></b> (🥈33 · ⭐ 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) (👨‍💻 74 · 🔀 190 · 📦 3.3K · 📋 890 - 15% open · ⏱️ 23.04.2025): ``` git clone https://github.com/serge-sans-paille/pythran ``` - [PyPi](https://pypi.org/project/pythran) (📥 320K / month · 📦 21 · ⏱️ 31.10.2024): ``` pip install pythran ``` - [Conda](https://anaconda.org/conda-forge/pythran) (📥 1.1M · ⏱️ 22.04.2025): ``` conda install -c conda-forge pythran ``` </details> <details><summary><b><a href="https://github.com/tensorly/tensorly">tensorly</a></b> (🥈33 · ⭐ 1.6K) - TensorLy: Tensor Learning in Python. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary> - [GitHub](https://github.com/tensorly/tensorly) (👨‍💻 72 · 🔀 290 · 📦 990 · 📋 280 - 23% open · ⏱️ 22.04.2025): ``` git clone https://github.com/tensorly/tensorly ``` - [PyPi](https://pypi.org/project/tensorly) (📥 76K / month · 📦 99 · ⏱️ 12.11.2024): ``` pip install tensorly ``` - [Conda](https://anaconda.org/conda-forge/tensorly) (📥 370K · ⏱️ 22.04.2025): ``` conda install -c conda-forge tensorly ``` </details> <details><summary><b><a href="https://github.com/pyjanitor-devs/pyjanitor">pyjanitor</a></b> (🥈32 · ⭐ 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) (👨‍💻 110 · 🔀 170 · 📦 920 · 📋 580 - 19% open · ⏱️ 22.04.2025): ``` git clone https://github.com/pyjanitor-devs/pyjanitor ``` - [PyPi](https://pypi.org/project/pyjanitor) (📥 93K / month · 📦 42 · ⏱️ 07.03.2025): ``` pip install pyjanitor ``` - [Conda](https://anaconda.org/conda-forge/pyjanitor) (📥 260K · ⏱️ 22.04.2025): ``` conda install -c conda-forge pyjanitor ``` </details> <details><summary><b><a href="https://github.com/PaddlePaddle/PaddleHub">PaddleHub</a></b> (🥈31 · ⭐ 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) (👨‍💻 70 · 🔀 2.1K · 📥 840 · 📦 1.9K · 📋 1.3K - 44% open · ⏱️ 07.08.2024): ``` git clone https://github.com/PaddlePaddle/PaddleHub ``` - [PyPi](https://pypi.org/project/paddlehub) (📥 6.8K / month · 📦 7 · ⏱️ 20.09.2023): ``` pip install paddlehub ``` </details> <details><summary><b><a href="https://github.com/online-ml/river">River</a></b> (🥈31 · ⭐ 5.3K) - Online machine learning in Python. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code></summary> - [GitHub](https://github.com/online-ml/river) (👨‍💻 120 · 🔀 560 · 📦 710 · 📋 620 - 19% open · ⏱️ 03.03.2025): ``` git clone https://github.com/online-ml/river ``` - [PyPi](https://pypi.org/project/river) (📥 83K / month · 📦 64 · ⏱️ 25.11.2024): ``` pip install river ``` - [Conda](https://anaconda.org/conda-forge/river) (📥 110K · ⏱️ 22.04.2025): ``` conda install -c conda-forge river ``` </details> <details><summary><b><a href="https://github.com/dstackai/dstack">dstack</a></b> (🥈31 · ⭐ 1.8K) - dstack is an open-source alternative to Kubernetes and Slurm, designed.. <code><a href="http://bit.ly/3postzC">MPL-2.0</a></code></summary> - [GitHub](https://github.com/dstackai/dstack) (👨‍💻 52 · 🔀 170 · 📦 18 · 📋 1.3K - 8% open · ⏱️ 24.04.2025): ``` git clone https://github.com/dstackai/dstack ``` - [PyPi](https://pypi.org/project/dstack) (📥 11K / month · ⏱️ 23.04.2025): ``` pip install dstack ``` </details> <details><summary><b><a href="https://github.com/open-edge-platform/anomalib">anomalib</a></b> (🥈30 · ⭐ 4.2K) - 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/open-edge-platform/anomalib) (👨‍💻 84 · 🔀 720 · 📥 24K · 📦 170 · 📋 1K - 15% open · ⏱️ 13.04.2025): ``` git clone https://github.com/openvinotoolkit/anomalib ``` - [PyPi](https://pypi.org/project/anomalib) (📥 72K / month · 📦 5 · ⏱️ 19.03.2025): ``` pip install anomalib ``` </details> <details><summary><b><a href="https://github.com/inducer/pyopencl">pyopencl</a></b> (🥈30 · ⭐ 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) (👨‍💻 98 · 🔀 240 · 📦 2.2K · 📋 360 - 21% open · ⏱️ 06.04.2025): ``` git clone https://github.com/inducer/pyopencl ``` - [PyPi](https://pypi.org/project/pyopencl) (📥 89K / month · 📦 180 · ⏱️ 22.01.2025): ``` pip install pyopencl ``` - [Conda](https://anaconda.org/conda-forge/pyopencl) (📥 1.7M · ⏱️ 22.04.2025): ``` conda install -c conda-forge pyopencl ``` </details> <details><summary><b><a href="https://github.com/datalad/datalad">datalad</a></b> (🥈30 · ⭐ 570) - 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) (👨‍💻 57 · 🔀 110 · 📦 520 · 📋 4K - 13% open · ⏱️ 15.12.2024): ``` git clone https://github.com/datalad/datalad ``` - [PyPi](https://pypi.org/project/datalad) (📥 21K / month · 📦 99 · ⏱️ 15.12.2024): ``` pip install datalad ``` - [Conda](https://anaconda.org/conda-forge/datalad) (📥 850K · ⏱️ 22.04.2025): ``` conda install -c conda-forge datalad ``` </details> <details><summary><b><a href="https://github.com/uber/causalml">causalml</a></b> (🥈29 · ⭐ 5.4K) - 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) (👨‍💻 65 · 🔀 810 · 📦 270 · 📋 410 - 10% open · ⏱️ 23.03.2025): ``` git clone https://github.com/uber/causalml ``` - [PyPi](https://pypi.org/project/causalml) (📥 43K / month · 📦 9 · ⏱️ 20.02.2025): ``` pip install causalml ``` </details> <details><summary><b><a href="https://github.com/google/trax">Trax</a></b> (🥉28 · ⭐ 8.2K) - 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) (👨‍💻 81 · 🔀 820 · 📦 220 · 📋 250 - 49% open · ⏱️ 10.04.2025): ``` git clone https://github.com/google/trax ``` - [PyPi](https://pypi.org/project/trax) (📥 4.5K / month · 📦 1 · ⏱️ 26.10.2021): ``` pip install trax ``` </details> <details><summary><b><a href="https://github.com/adapter-hub/adapters">adapter-transformers</a></b> (🥉28 · ⭐ 2.7K) - 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) (👨‍💻 16 · 🔀 360 · 📦 200 · 📋 400 - 10% open · ⏱️ 19.04.2025): ``` git clone https://github.com/Adapter-Hub/adapter-transformers ``` - [PyPi](https://pypi.org/project/adapter-transformers) (📥 5.4K / month · 📦 12 · ⏱️ 07.07.2024): ``` pip install adapter-transformers ``` </details> <details><summary><b><a href="https://github.com/ContinualAI/avalanche">avalanche</a></b> (🥉28 · ⭐ 1.9K) - 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) (👨‍💻 85 · 🔀 300 · 📥 53 · 📦 130 · 📋 830 - 12% open · ⏱️ 11.03.2025): ``` git clone https://github.com/ContinualAI/avalanche ``` - [PyPi](https://pypi.org/project/avalanche-lib) (📥 2K / month · 📦 3 · ⏱️ 29.10.2024): ``` pip install avalanche-lib ``` </details> <details><summary><b><a href="https://github.com/tableau/TabPy">TabPy</a></b> (🥉28 · ⭐ 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) (👨‍💻 51 · 🔀 600 · 📦 210 · 📋 320 - 6% open · ⏱️ 25.11.2024): ``` git clone https://github.com/tableau/TabPy ``` - [PyPi](https://pypi.org/project/tabpy) (📥 7.6K / month · 📦 2 · ⏱️ 25.11.2024): ``` pip install tabpy ``` - [Conda](https://anaconda.org/anaconda/tabpy-client) (📥 5.1K · ⏱️ 22.04.2025): ``` conda install -c anaconda tabpy-client ``` </details> <details><summary><b><a href="https://github.com/MaxHalford/prince">Prince</a></b> (🥉28 · ⭐ 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) (👨‍💻 16 · 🔀 180 · 📦 710 · ⏱️ 09.03.2025): ``` git clone https://github.com/MaxHalford/prince ``` - [PyPi](https://pypi.org/project/prince) (📥 180K / month · 📦 20 · ⏱️ 09.03.2025): ``` pip install prince ``` - [Conda](https://anaconda.org/conda-forge/prince-factor-analysis) (📥 24K · ⏱️ 22.04.2025): ``` conda install -c conda-forge prince-factor-analysis ``` </details> <details><summary><b><a href="https://github.com/sepandhaghighi/pycm">pycm</a></b> (🥉27 · ⭐ 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) (👨‍💻 18 · 🔀 130 · 📦 390 · 📋 210 - 8% open · ⏱️ 04.04.2025): ``` git clone https://github.com/sepandhaghighi/pycm ``` - [PyPi](https://pypi.org/project/pycm) (📥 38K / month · 📦 24 · ⏱️ 04.04.2025): ``` pip install pycm ``` </details> <details><summary><b><a href="https://github.com/scikit-learn-contrib/metric-learn">metric-learn</a></b> (🥉26 · ⭐ 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) (👨‍💻 23 · 🔀 230 · 📦 470 · 📋 180 - 30% open · ⏱️ 03.08.2024): ``` git clone https://github.com/scikit-learn-contrib/metric-learn ``` - [PyPi](https://pypi.org/project/metric-learn) (📥 6.4K / month · 📦 7 · ⏱️ 09.10.2023): ``` pip install metric-learn ``` - [Conda](https://anaconda.org/conda-forge/metric-learn) (📥 16K · ⏱️ 22.04.2025): ``` conda install -c conda-forge metric-learn ``` </details> <details><summary><b><a href="https://github.com/facebookresearch/AugLy">AugLy</a></b> (🥉25 · ⭐ 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) (👨‍💻 38 · 🔀 300 · 📦 170 · 📋 80 - 30% open · ⏱️ 28.02.2025): ``` git clone https://github.com/facebookresearch/AugLy ``` - [PyPi](https://pypi.org/project/augly) (📥 2.9K / month · 📦 4 · ⏱️ 05.12.2023): ``` pip install augly ``` </details> <details><summary><b><a href="https://github.com/solegalli/feature_engine">Feature Engine</a></b> (🥉25 · ⭐ 2K · 💤) - 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) (👨‍💻 49 · 🔀 320 · ⏱️ 31.08.2024): ``` git clone https://github.com/solegalli/feature_engine ``` - [PyPi](https://pypi.org/project/feature_engine) (📥 260K / month · 📦 180 · ⏱️ 22.01.2025): ``` pip install feature_engine ``` - [Conda](https://anaconda.org/conda-forge/feature_engine) (📥 71K · ⏱️ 22.04.2025): ``` conda install -c conda-forge feature_engine ``` </details> <details><summary><b><a href="https://github.com/BioPandas/biopandas">BioPandas</a></b> (🥉23 · ⭐ 730 · 💤) - 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) (👨‍💻 18 · 🔀 120 · 📦 360 · 📋 60 - 36% open · ⏱️ 01.08.2024): ``` git clone https://github.com/rasbt/biopandas ``` - [PyPi](https://pypi.org/project/biopandas) (📥 11K / month · 📦 38 · ⏱️ 01.08.2024): ``` pip install biopandas ``` - [Conda](https://anaconda.org/conda-forge/biopandas) (📥 180K · ⏱️ 22.04.2025): ``` conda install -c conda-forge biopandas ``` </details> <details><summary><b><a href="https://github.com/pykale/pykale">pykale</a></b> (🥉22 · ⭐ 460) - 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) (👨‍💻 26 · 🔀 66 · 📦 6 · 📋 130 - 8% open · ⏱️ 24.04.2025): ``` git clone https://github.com/pykale/pykale ``` - [PyPi](https://pypi.org/project/pykale) (📥 410 / month · ⏱️ 12.04.2022): ``` pip install pykale ``` </details> <details><summary><b><a href="https://github.com/yzhao062/SUOD">SUOD</a></b> (🥉22 · ⭐ 380) - (MLSys 21) An Acceleration System for Large-scare Unsupervised Heterogeneous.. <code><a href="http://bit.ly/3rqEWVr">BSD-2</a></code></summary> - [GitHub](https://github.com/yzhao062/SUOD) (👨‍💻 3 · 🔀 49 · 📦 550 · 📋 15 - 80% open · ⏱️ 24.03.2025): ``` git clone https://github.com/yzhao062/SUOD ``` - [PyPi](https://pypi.org/project/suod) (📥 11K / month · 📦 9 · ⏱️ 24.03.2025): ``` pip install suod ``` </details> <details><summary><b><a href="https://github.com/clementchadebec/benchmark_VAE">benchmark_VAE</a></b> (🥉21 · ⭐ 1.9K · 💤) - Unifying Variational Autoencoder (VAE).. <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) (👨‍💻 18 · 🔀 170 · 📦 40 · 📋 71 - 36% open · ⏱️ 17.07.2024): ``` git clone https://github.com/clementchadebec/benchmark_VAE ``` - [PyPi](https://pypi.org/project/pythae) (📥 1.2K / month · ⏱️ 06.09.2023): ``` pip install pythae ``` </details> <details><summary><b><a href="https://github.com/Project-MONAI/MONAILabel">MONAILabel</a></b> (🥉21 · ⭐ 700) - 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) (👨‍💻 66 · 🔀 220 · 📥 110K · 📋 540 - 25% open · ⏱️ 03.04.2025): ``` git clone https://github.com/Project-MONAI/MONAILabel ``` - [PyPi](https://pypi.org/project/monailabel-weekly) (📥 1.7K / month · ⏱️ 01.10.2023): ``` pip install monailabel-weekly ``` </details> <details><summary><b><a href="https://github.com/infer-actively/pymdp">pymdp</a></b> (🥉20 · ⭐ 520) - 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) (👨‍💻 19 · 🔀 100 · 📦 20 · 📋 53 - 49% open · ⏱️ 06.02.2025): ``` git clone https://github.com/infer-actively/pymdp ``` - [PyPi](https://pypi.org/project/inferactively-pymdp) (📥 7.2K / month · ⏱️ 08.12.2022): ``` pip install inferactively-pymdp ``` </details> <details><summary><b><a href="https://github.com/facebookresearch/NeuralCompression">NeuralCompression</a></b> (🥉15 · ⭐ 550 · 💤) - 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) (👨‍💻 10 · 🔀 45 · 📋 71 - 7% open · ⏱️ 20.09.2024): ``` git clone https://github.com/facebookresearch/NeuralCompression ``` - [PyPi](https://pypi.org/project/neuralcompression) (📥 310 / month · ⏱️ 03.10.2023): ``` pip install neuralcompression ``` </details> <details><summary>Show 28 hidden projects...</summary> - <b><a href="https://github.com/cleanlab/cleanlab">cleanlab</a></b> (🥈31 · ⭐ 10K) - The standard data-centric AI package for data quality and machine.. <code><a href="http://bit.ly/3pwmjO5">❗️AGPL-3.0</a></code> - <b><a href="https://github.com/explosion/cython-blis">Cython BLIS</a></b> (🥈31 · ⭐ 230) - 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/google-deepmind/pysc2">pysc2</a></b> (🥈29 · ⭐ 8.1K · 💀) - StarCraft II Learning Environment. <code><a href="http://bit.ly/3nYMfla">Apache-2</a></code> - <b><a href="https://github.com/JustGlowing/minisom">minisom</a></b> (🥈29 · ⭐ 1.5K) - MiniSom is a minimalistic implementation of the Self Organizing.. <code><a href="https://tldrlegal.com/search?q=CC-BY-3.0">❗️CC-BY-3.0</a></code> - <b><a href="https://github.com/nicodv/kmodes">kmodes</a></b> (🥈29 · ⭐ 1.3K · 💀) - Python implementations of the k-modes and k-prototypes clustering.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/annoviko/pyclustering">pyclustering</a></b> (🥈29 · ⭐ 1.2K · 💀) - pyclustering is a Python, C++ data mining library. <code><a href="http://bit.ly/3aKzpTv">BSD-3</a></code> - <b><a href="https://github.com/SeldonIO/alibi-detect">alibi-detect</a></b> (🥉28 · ⭐ 2.3K) - Algorithms for outlier, adversarial and drift detection. <code><a href="https://tldrlegal.com/search?q=Intel">❗️Intel</a></code> - <b><a href="https://github.com/modAL-python/modAL">modAL</a></b> (🥉28 · ⭐ 2.3K · 💀) - 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/trevorstephens/gplearn">gplearn</a></b> (🥉27 · ⭐ 1.7K · 💀) - 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/ljvmiranda921/pyswarms">PySwarms</a></b> (🥉27 · ⭐ 1.3K · 💀) - 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/dbt-labs/metricflow">metricflow</a></b> (🥉27 · ⭐ 1.2K) - MetricFlow allows you to define, build, and maintain metrics.. <code>❗Unlicensed</code> - <b><a href="https://github.com/sinaptik-ai/pandas-ai">pandas-ai</a></b> (🥉25 · ⭐ 20K) - Chat with your database or your datalake (SQL, CSV, parquet)... <code>❗Unlicensed</code> - <b><a href="https://github.com/minrk/findspark">findspark</a></b> (🥉25 · ⭐ 520 · 💀) - 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/mars-project/mars">Mars</a></b> (🥉24 · ⭐ 2.7K · 💀) - 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/astroML/astroML">AstroML</a></b> (🥉23 · ⭐ 1.1K · 💀) - 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> - <b><a href="https://github.com/vecxoz/vecstack">vecstack</a></b> (🥉23 · ⭐ 690 · 💀) - Python package for stacking (machine learning technique). <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/ml-tooling/opyrator">opyrator</a></b> (🥉22 · ⭐ 3.1K · 💀) - 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> (🥉22 · ⭐ 850 · 💀) - ML-Ensemble high performance ensemble learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/jmschrei/apricot">apricot</a></b> (🥉22 · ⭐ 500 · 💀) - apricot implements submodular optimization for the purpose of.. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/eltonlaw/impyute">impyute</a></b> (🥉21 · ⭐ 360 · 💀) - 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> (🥉20 · ⭐ 2.9K · 💀) - 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> (🥉20 · ⭐ 510 · 💀) - 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/EpistasisLab/scikit-rebate">scikit-rebate</a></b> (🥉20 · ⭐ 420 · 💀) - 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/alegonz/baikal">baikal</a></b> (🥉19 · ⭐ 590 · 💀) - 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/SforAiDl/KD_Lib">KD-Lib</a></b> (🥉16 · ⭐ 620 · 💀) - 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> (🥉16 · ⭐ 320 · 💀) - 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/Palashio/nylon">nylon</a></b> (🥉14 · ⭐ 83 · 💀) - An intelligent, flexible grammar of machine learning. <code><a href="http://bit.ly/34MBwT8">MIT</a></code> - <b><a href="https://github.com/jrieke/traingenerator">traingenerator</a></b> (🥉13 · ⭐ 1.4K · 💀) - A web app to generate template code for 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 [](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"