A curated list of awesome Machine Learning frameworks, libraries and software.
High-level wrapper built on the top of Pytorch which supports vision, text, tabular data and collaborative filtering.
Naive Bayesian Classifier implementation in APL. [Deprecated]
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.
A C library for product recommendations/suggestions using collaborative filtering (CF).
A hybrid recommender system based upon scikit-learn algorithms. [Deprecated]
A lightweight, portable pure C99 onnx inference engine for embedded devices with hardware acceleration support.
DLib has C++ and Python interfaces for face detection and training general object detectors.
VLFeat is an open and portable library of computer vision algorithms, which has a Matlab toolbox.
Eblearn is an object-oriented C++ library that implements various machine learning models [Deprecated]
C-based/Cached/Core Computer Vision Library, A Modern Computer Vision Library.
Python bindings for the VIGRA C++ computer vision library.
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.
OpenCV has C++, C, Python, Java and MATLAB interfaces and supports Windows, Linux, Android and Mac OS.
This is a fast C++/CUDA implementation of convolutional [DEEP LEARNING]
A simple Multi-armed Bandit library. [Deprecated]
General purpose gradient boosting on decision trees library with categorical features support out of the box for R.
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.
A real-time multi-person keypoint detection library for body, face, hands, and foot estimation
A software library created by Amazon for training and deploying deep neural networks using GPUs which emphasizes speed and scale over experimental flexibility.
Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit. Documentation can be found here.