A curated list of awesome Machine Learning frameworks, libraries and software.
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:
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.
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.illinois-core-utilities
which provides a set of NLP-friendly data structures and a number of NLP-related utilities that support writing NLP applications, running experiments, etc, illinois-edison
a library for feature extraction from illinois-core-utilities data structures and many other packages.AI
namespace. For instance, you can
find Naïve Bayes.L0CV
, is a new generation of computer vision open source online learning media, a cross-platform interactive learning framework integrating graphics, source code and HTML. the L0CV ecosystem — Notebook, Datasets, Source Code, and from Diving-in to Advanced — as well as the L0CV Hub.transformers
.logger.log()
.linfa
aims to provide a comprehensive toolkit to build Machine Learning applications with Rust