awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
Awesome Machine Learning is a comprehensive collection of machine learning frameworks, libraries, and tools organized by programming language. Curated by Joseph Misiti, this repository serves as a central reference point for developers seeking ML resources across 30+ languages including Python, C++, Java, JavaScript, R, and more. The collection covers specialized categories such as computer vision, natural language processing, deep learning, data analysis, and reinforcement learning, along with supplementary resources including free books, courses, blogs, and events.
Key Features
Use Cases
- 01Discovering ML libraries and frameworks for a specific programming language or domain
- 02Comparing computer vision tools like OpenCV, VIGRA, and YOLOv8 for image processing projects
- 03Finding NLP resources across languages including tokenizers, parsers, and language models
- 04Identifying deep learning frameworks with GPU support for training neural networks
- 05Locating free educational resources including books, courses, and tutorials for learning ML
- 06Selecting gradient boosting libraries like XGBoost, LightGBM, or CatBoost for tabular data
awesome-machine-learning — FAQ
What is awesome-machine-learning?+
Awesome Machine Learning is a curated directory of machine learning frameworks, libraries, and software organized by programming language. It includes resources for deep learning, computer vision, NLP, data analysis, and supplementary materials like free books and courses.
How do I use this resource?+
Navigate to the GitHub repository and browse the table of contents organized by programming language and ML domain. Each entry includes a brief description and link to the project repository or documentation.
Does awesome-machine-learning require installation?+
No, this is a curated list resource, not installable software. It provides links to ML libraries and frameworks that you can then install individually based on your needs.
Is awesome-machine-learning free to use?+
Yes, the list itself is freely available on GitHub. Individual libraries linked in the collection have their own licenses, though most are open source.
Which programming languages are covered?+
The collection covers 30+ languages including Python, C++, Java, JavaScript, R, Julia, Go, Rust, Scala, Swift, Ruby, and many others, each with categorized ML resources.
How can I contribute to the list?+
As of April 2026, contributors must email the maintainer to verify they are human before submitting pull requests, due to an influx of LLM-generated contributions.
How do I install awesome-machine-learning?+
Open the source repository on GitHub and follow its README. awesome-machine-learning is a skill — MCP Agents Market links you directly to the official repo.
Is awesome-machine-learning free?+
awesome-machine-learning is an open-source project hosted on GitHub. Check the repository for its license and any usage requirements.