h2oai/h2o4gpu

NVIDIA cuML: GPU-Accelerated Machine Learning

Extension for Scikit-learn is a seamless way to speed up your Scikit-learn application

A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.

Fast and memory-efficient classical machine learning operators

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

Tensors and Dynamic neural networks in Python with strong GPU acceleration

⚡ TabPFN: Foundation Model for Tabular Data ⚡

scikit-learn: machine learning in Python

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.