This repository curates a comprehensive collection of AI-related books, papers, and learning resources, targeting individuals seeking to deepen their understanding of artificial intelligence. It provides direct links to PDFs and online materials covering foundational mathematics, machine learning, deep learning, NLP, computer vision, and more, aiming to serve as a centralized hub for AI education.

How It Works

The repository organizes resources into logical categories, including "Introductory theory," "Mathematics," "Data mining," "Machine Learning," "Deep Learning," and specialized areas like "Reinforcement Learning," "NLP," and "CV." It also links to various "Training ground" environments and frameworks, such as OpenAI Gym, DeepMind's PySC2, and Google's Dopamine, facilitating hands-on experimentation with AI algorithms. Many book PDFs are hosted on Yandex.Disk due to GitHub's file size limitations.

Quick Start & Requirements

• Access to the listed books and papers requires navigating to the provided links, many of which point to external hosting services like Yandex.Disk or directly to online interactive books.
• Some "Training ground" environments may have specific installation requirements (e.g., Python, specific libraries like TensorFlow or PyTorch, game clients like StarCraft II or Minecraft).
• Links to official documentation and demos are provided for many of the listed frameworks and libraries.

Highlighted Details

• Extensive coverage of foundational AI topics, including mathematics, data mining, and core ML/DL concepts.
• Curated list of popular AI research papers and their associated code repositories.
• Links to interactive learning environments and frameworks for practical AI development.
• Includes both English and Chinese language resources for key texts like "Dive into Deep Learning."

Maintenance & Community

The project welcomes contributions via issues and pull requests for adding new books or suggesting improvements. Financial and organizational contributions are also encouraged to sustain the community.

Licensing & Compatibility

The README explicitly states: "This repo only used for learning, do not use in business." This suggests a non-commercial use limitation, though specific licenses for individual books or papers are not detailed.

Limitations & Caveats

The primary caveat is the explicit non-commercial use restriction. Additionally, reliance on external hosting for many PDF files means availability is subject to those services. The project's scope is broad, and while comprehensive, it may not cover every niche AI subfield.