Awesome Python Data Science

An Open Source Machine Learning Framework for Everyone

Tensors and Dynamic neural networks in Python with strong GPU acceleration

Open Source Computer Vision Library

Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

Caffe: a fast open framework for deep learning.

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

A game theoretic approach to explain the output of any machine learning model.

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）

Graph Neural Network Library for PyTorch

Open standard for machine learning interoperability

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

Datasets, Transforms and Models specific to Computer Vision

Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

A toolkit for making real world machine learning and data analysis applications in C++

Python package built to ease deep learning on graph, on top of existing DL frameworks.

cuDF - GPU DataFrame Library

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.

Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀

Qiskit is an open-source SDK for working with quantum computers at the level of extended quantum circuits, operators, and primitives.

Flax is a neural network library for JAX that is designed for flexibility.

mlpack: a fast, header-only C++ machine learning library

cuML - RAPIDS Machine Learning Library

a library for audio and music analysis

A platform for Reasoning systems (Reinforcement Learning, Contextual Bandits, etc.)

Models, data loaders and abstractions for language processing, powered by PyTorch

High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

Shōgun

Data manipulation and transformation for audio signal processing, powered by PyTorch

Neural Network Libraries

An efficient video loader for deep learning with smart shuffling that's super easy to digest

library for nonlinear optimization, wrapping many algorithms for global and local, constrained or unconstrained, optimization

ThunderSVM: A Fast SVM Library on GPUs and CPUs

Universal model exchange and serialization format for decision tree forests

ThunderGBM: Fast GBDTs and Random Forests on GPUs

TensorFlow ROCm port

Module for statistical learning, with a particular emphasis on time-dependent modelling

Marsyas - Music Analysis, Retrieval and Synthesis for Audio Signals

An engine for high performance multi-agent environments with very large numbers of agents, along with a set of reference environments

Audio features extraction