(Paperback)
By: Robert E. Schapire
ISBN: 9780262526036
Readership/Audience: Professional and Scholarly
Publication Date: Jan 2014
Publisher: MIT Press Ltd
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An accessible introduction and essential reference for an approach to machine learning that creates highly accurate prediction rules by combining many weak and inaccurate ones.
(Paperback)
By: Ralf Herbrich
ISBN: 9780262546591
Readership/Audience: Professional and Scholarly
Publication Date: Nov 2022
Publisher: MIT Press Ltd
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(Paperback)
By: Bernhard Schlkopf
ISBN: 9780262536578
Readership/Audience: Professional and Scholarly
Publication Date: Jun 2018
Publisher: MIT Press Ltd
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A comprehensive introduction to Support Vector Machines and related kernel methods.
(Paperback)
By: Albert Bifet
ISBN: 9780262547833
Readership/Audience: General
Publication Date: May 2023
Publisher: MIT Press Ltd
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(Paperback)
By: Peter D. Grnwald
ISBN: 9780262529631
Readership/Audience: Professional and Scholarly
Publication Date: Mar 2007
Publisher: MIT Press Ltd
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A comprehensive introduction and reference guide to the minimum description length (MDL) Principle that is accessible to researchers dealing with inductive reference in diverse areas including statistics, pattern classification, machine learning, data mining, biology, econometrics, and experimental psychology, as well as philosophers interested in the foundations of statistics.
(Hardback, second edition)
By: Pierre Baldi
ISBN: 9780262025065
Readership/Audience: Tertiary Education
Publication Date: Jul 2001
Publisher: MIT Press Ltd
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A guide to machine learning approaches and their application to the analysis of biological data.
(Hardback)
By: Jonas Peters
ISBN: 9780262037310
Readership/Audience: Tertiary Education
Publication Date: Nov 2017
Publisher: MIT Press Ltd
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A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning.
(Hardback, second edition)
By: Mehryar Mohri
ISBN: 9780262039406
Readership/Audience: Tertiary Education
Publication Date: Dec 2018
Publisher: MIT Press Ltd
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A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms.
(Hardback)
By: Carl Edward Rasmussen
ISBN: 9780262182539
Readership/Audience: Professional and Scholarly
Publication Date: Nov 2005
Publisher: MIT Press Ltd
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A comprehensive and self-contained introduction to Gaussian processes, which provide a principled, practical, probabilistic approach to learning in kernel machines.
(Hardback)
By: Jacob Eisenstein
ISBN: 9780262042840
Readership/Audience: Tertiary Education
Publication Date: Oct 2019
Publisher: MIT Press Ltd
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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)
By: Elad Hazan
ISBN: 9780262046985
Readership/Audience: General
Publication Date: Nov 2022
Publisher: MIT Press Ltd
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(Hardback)
By: Masashi Sugiyama
ISBN: 9780262047074
Readership/Audience: General
Publication Date: Oct 2022
Publisher: MIT Press Ltd
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"An overview of machine learning from data that is easily collectible, but challenging to annotate for learning algorithms"--
(Hardback, second edition)
By: Richard S. Sutton
ISBN: 9780262039246
Readership/Audience: Tertiary Education
Publication Date: Nov 2018
Publisher: MIT Press Ltd
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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.
