This repository is a comprehensive, curated list of "awesome lists" covering a vast spectrum of machine learning and deep learning topics. It serves as a valuable resource for beginners seeking to understand ML branches, researchers tracking new directions, and engineers looking for practical tools and tutorials.

How It Works

The project functions as a meta-list, aggregating and organizing links to other curated lists, libraries, papers, and tutorials. It categorizes resources by ML paradigms (e.g., Reinforcement Learning, Meta-learning), tasks and applications (e.g., Computer Vision, NLP), specific model types (e.g., GNNs, GANs), and interdisciplinary areas. The structure allows for easy navigation and discovery of specialized knowledge.

Quick Start & Requirements

This is a curated list, not a software package. No installation or execution is required. Users access the resources by browsing the Markdown file.

Highlighted Details

• Extensive coverage: Includes 380+ items as of Dec 2021, spanning numerous ML subfields.
• Dual language support: Available in both English and Chinese.
• Active maintenance: Regularly updated with new sections and content (last update Jan 2023).
• Community contribution: Encourages contributions via issues and pull requests, with a clear contribution guide.

Maintenance & Community

The project is maintained by Zhining Liu and includes contributions from several individuals. It encourages community involvement through GitHub issues and pull requests.

Licensing & Compatibility

The repository itself is not software and therefore not subject to software licensing. The linked resources will have their own respective licenses.

Limitations & Caveats

Some linked lists are marked as "[⚠️Inactive]", indicating they have not been updated for over 12 months, though they may still be valuable references. The sheer volume of resources means users will need to filter and evaluate individual links.