(Hardback)

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives.

(Hardback, second edition)

A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms.

(Hardback)

A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines.

(Hardback, fourth edition)

A substantially revised fourth edition of a comprehensive textbook, including new coverage of recent advances in deep learning and neural networks.

(Hardback)

A survey of computational methods for understanding, generating, and manipulating human language, which offers a synthesis of classical representations and algorithms with contemporary machine learning techniques.

(Hardback)

(Hardback)

"An overview of machine learning from data that is easily collectible, but challenging to annotate for learning algorithms"--

(Hardback, second edition)

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence.