Awesome Machine Learning

A curated list of awesome machine learning frameworks, libraries and software (by language). Inspired by awesome-php.

If you want to contribute to this list (please do), send me a pull request or contact me @josephmisiti. Also, a listed repository should be deprecated if:

Repository's owner explicitly says that "this library is not maintained".
Not committed for a long time (2~3 years).

Further resources:

For a list of free machine learning books available for download, go here.
For a list of professional machine learning events, go here.
For a list of (mostly) free machine learning courses available online, go here.
For a list of blogs and newsletters on data science and machine learning, go here.
For a list of free-to-attend meetups and local events, go here.

Frameworks and Libraries

Awesome Machine Learning

Credits

APL

General-Purpose Machine Learning

naive-apl - Naive Bayesian Classifier implementation in APL. [Deprecated]

C

General-Purpose Machine Learning

Darknet - Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation.
Recommender - A C library for product recommendations/suggestions using collaborative filtering (CF).
Hybrid Recommender System - A hybrid recommender system based upon scikit-learn algorithms. [Deprecated]
neonrvm - neonrvm is an open source machine learning library based on RVM technique. It's written in C programming language and comes with Python programming language bindings.
cONNXr - An ONNX runtime written in pure C (99) with zero dependencies focused on small embedded devices. Run inference on your machine learning models no matter which framework you train it with. Easy to install and compiles everywhere, even in very old devices.
libonnx - A lightweight, portable pure C99 onnx inference engine for embedded devices with hardware acceleration support.

Computer Vision

CCV - C-based/Cached/Core Computer Vision Library, A Modern Computer Vision Library.
VLFeat - VLFeat is an open and portable library of computer vision algorithms, which has a Matlab toolbox.

C++

Computer Vision

DLib - DLib has C++ and Python interfaces for face detection and training general object detectors.
EBLearn - Eblearn is an object-oriented C++ library that implements various machine learning models [Deprecated]
OpenCV - OpenCV has C++, C, Python, Java and MATLAB interfaces and supports Windows, Linux, Android and Mac OS.
VIGRA - VIGRA is a genertic cross-platform C++ computer vision and machine learning library for volumes of arbitrary dimensionality with Python bindings.
Openpose - A real-time multi-person keypoint detection library for body, face, hands, and foot estimation

General-Purpose Machine Learning

Speedster -Automatically apply SOTA optimization techniques to achieve the maximum inference speed-up on your hardware. [DEEP LEARNING]
BanditLib - A simple Multi-armed Bandit library. [Deprecated]
Caffe - A deep learning framework developed with cleanliness, readability, and speed in mind. [DEEP LEARNING]
CatBoost - General purpose gradient boosting on decision trees library with categorical features support out of the box. It is easy to install, contains fast inference implementation and supports CPU and GPU (even multi-GPU) computation.
CNTK - The Computational Network Toolkit (CNTK) by Microsoft Research, is a unified deep-learning toolkit that describes neural networks as a series of computational steps via a directed graph.
CUDA - This is a fast C++/CUDA implementation of convolutional [DEEP LEARNING]
DeepDetect - A machine learning API and server written in C++11. It makes state of the art machine learning easy to work with and integrate into existing applications.
Distributed Machine learning Tool Kit (DMTK) - A distributed machine learning (parameter server) framework by Microsoft. Enables training models on large data sets across multiple machines. Current tools bundled with it include: LightLDA and Distributed (Multisense) Word Embedding.
DLib - A suite of ML tools designed to be easy to imbed in other applications.
DSSTNE - A software library created by Amazon for training and deploying deep neural networks using GPUs which emphasizes speed and scale over experimental flexibility.
DyNet - A dynamic neural network library working well with networks that have dynamic structures that change for every training instance. Written in C++ with bindings in Python.
Fido - A highly-modular C++ machine learning library for embedded electronics and robotics.
igraph - General purpose graph library.
Intel® oneAPI Data Analytics Library - A high performance software library developed by Intel and optimized for Intel's architectures. Library provides algorithmic building blocks for all stages of data analytics and allows to process data in batch, online and distributed modes.
LightGBM - Microsoft's fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
libfm - A generic approach that allows to mimic most factorization models by feature engineering.
MLDB - The Machine Learning Database is a database designed for machine learning. Send it commands over a RESTful API to store data, explore it using SQL, then train machine learning models and expose them as APIs.
mlpack - A scalable C++ machine learning library.
MXNet - Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Go, JavaScript and more.
N2D2 - CEA-List's CAD framework for designing and simulating Deep Neural Network, and building full DNN-based applications on embedded platforms
oneDNN - An open-source cross-platform performance library for deep learning applications.
ParaMonte - A general-purpose library with C/C++ interface for Bayesian data analysis and visualization via serial/parallel Monte Carlo and MCMC simulations. Documentation can be found here.