A curated list of free, legitimately accessible books on Deep Learning, Reinforcement Learning, Probabilistic Machine Learning, NLP/LLMs, and mathematical foundations — all made officially available by their own authors or publishers.

Every link points to an official source. This repository doesn't host any files — it only organizes and catalogs what authors already offer for free. See why at the bottom.

• 🧠 Deep Learning
• 🎮 Reinforcement Learning
• 📊 Probabilistic / Bayesian
• 📈 Classical Machine Learning / Statistics
• 🗣️ NLP / LLMs
• 🧮 Mathematics for ML
• 🖥️ ML Systems / Infrastructure
• 👁️ Computer Vision
• 🎨 Generative Models (Diffusion, GANs, VAEs)
• 🔗 Causal Inference
• 🕸️ Graph Neural Networks
• 🛡️ AI Safety / Alignment
• 🎓 Advanced RL / Theory
• How to Contribute
• Why Official Links Only

Contributions are welcome! Before opening a PR, read CONTRIBUTING.md. Quick rules:

1. The book must be officially and permanently free (no paid early-access, no time-limited trial).
2. The link must point to the primary source (author's site, university, or publisher with an open license) — never Scribd, PDFCoffee, Z-Library, Library Genesis, or similar.
3. Add it to the correct category, keeping alphabetical order by author within the table.
4. One book per PR to keep reviews easy.

This repository does not host any files. It works as a catalog/index, pointing to where authors themselves make their books freely available. This approach:

• Respects each author's license terms (some, like the Deep Learning Book, track reader numbers via their own site analytics).
• Avoids copyright issues and possible takedowns of the repository.
• Guarantees you always get the most up-to-date version (several of these books — like Speech and Language Processing and The Little Book of Deep Learning — are updated frequently).

If a link breaks, please open an issue.

Made with 📖 for the global AI/ML community.
Curated by Marcos Cruz — feel free to connect on LinkedIn.