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Books & Reading

Curated books, reading guides, and written resources from leading AI researchers and practitioners.

8 courses · all free to start

Books / Reading Sources

Goodfellow et al.

IntermediateFree Members

Deep Learning

The canonical deep learning textbook by Goodfellow, Bengio, and Courville — free online.

Books / Reading Sources

Simon Prince

IntermediateFree Members

Understanding Deep Learning

Visual and intuitive deep learning reference book by Simon J.D. Prince — free online.

Books / Reading Sources

Sutton & Barto

IntermediateFree Members

Reinforcement Learning: An Introduction

The foundational reinforcement learning text by Sutton and Barto — free official PDF.

Books / Reading Sources

Mohri

AdvancedFree Members

Foundations of Machine Learning

MIT Press canonical ML theory textbook by Mohri, Rostamizadeh, and Talwalkar — free PDF from authors.

Books / Reading Sources

Kevin Murphy

AdvancedFree Members

Probabilistic Machine Learning: An Introduction

Canonical probabilistic ML book by Kevin Murphy — free online.

Books / Reading Sources

Albrecht

AdvancedFree Members

Multi-Agent Reinforcement Learning: Foundations and Modern Approaches

Free official online textbook on MARL covering coordination, competition, and modern multi-agent systems.

Books / Reading Sources

Ankur Moitra

AdvancedFree Members

Algorithmic Aspects of Machine Learning

MIT CSAIL textbook and lecture notes by Ankur Moitra on algorithmic foundations of machine learning — free PDF.

Books / Reading Sources

Kevin Murphy

AdvancedFree Members

Probabilistic Machine Learning: Advanced Topics

Canonical probabilistic ML advanced topics book by Kevin Murphy — free online, covering deep generative models and inference.