josephmisiti/awesome-machine-learning

Awesome Machine Learning is a curated reference list of machine learning frameworks, libraries, and software tools, organized by programming language. The problem it solves is discovery: the machine learning ecosystem is enormous and fragmented across many languages and subfields, and finding the right library for a specific task in a specific language can be time-consuming. This list gathers vetted options in one place so developers and researchers can quickly find what exists without searching through countless individual repositories. The list is organized by programming language, covering a very wide range including Python, C++, Java, JavaScript, Julia, Go, R, Scala, Ruby, Rust, and many others. Within each language, entries are grouped by ML subfield such as general-purpose machine learning, computer vision, natural language processing, data analysis, deep learning, and reinforcement learning. Each entry is a link to the relevant library or tool with a brief description. Companion files cover free books, online courses, blogs, and events related to machine learning. The repository notes that as of April 2026 it requires human confirmation for pull requests due to an influx of LLM-generated contributions. You would use this repository when you are starting a new ML project and want to survey what libraries are available in your language of choice, when you are researching tools in a specific subfield, or when onboarding someone new to the ML ecosystem. It is not software you run; it is a reference document in Markdown format. The repository is part of the broader "awesome" list convention on GitHub, where curated topic lists are shared as structured Markdown files.