Foundations of Machine Learning (inbunden)
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Format
Inbunden (Hardback)
Språk
Engelska
Antal sidor
432
Utgivningsdatum
2012-08-17
Förlag
MIT Press
Medarbetare
Bach, Francis (series ed.)
Illustrationer
55 color illus., 40 b&w illus.; 95 Illustrations, unspecified
Dimensioner
241 x 196 x 31 mm
Vikt
1106 g
Antal komponenter
1
ISBN
9780262018258

Foundations of Machine Learning

av Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar
Inbunden,  Engelska, 2012-08-17
825
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Fundamental topics in machine learning are presented along with theoretical and conceptual tools for the discussion and proof of algorithms. This graduate-level textbook introduces fundamental concepts and methods in machine learning. It describes several important modern algorithms, provides the theoretical underpinnings of these algorithms, and illustrates key aspects for their application. The authors aim to present novel theoretical tools and concepts while giving concise proofs even for relatively advanced topics. Foundations of Machine Learning fills the need for a general textbook that also offers theoretical details and an emphasis on proofs. Certain topics that are often treated with insufficient attention are discussed in more detail here; for example, entire chapters are devoted to regression, multi-class classification, and ranking. The first three chapters lay the theoretical foundation for what follows, but each remaining chapter is mostly self-contained. The appendix offers a concise probability review, a short introduction to convex optimization, tools for concentration bounds, and several basic properties of matrices and norms used in the book. The book is intended for graduate students and researchers in machine learning, statistics, and related areas; it can be used either as a textbook or as a reference text for a research seminar.
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In my opinion, the content of the book is outstanding in terms of clarity of discourse and the variety of well-selected examples and exercises. The enlightening comments provided by the author at the end of each chapter and the suggestions for further reading are also important features of the book. The concepts and methods are presented in a very clear and accessible way and the illustrative examples contribute substantially to facilitating the understanding of the overall work. -Computing Reviews

Övrig information

Mehryar Mohri is Professor of Computer Science at New York University's Courant Institute of Mathematical Sciences and a Research Consultant at Google Research. Afshin Rostamizadeh is a Research Scientist at Google Research. Ameet Talwalkar is Assistant Professor in the Machine Learning Department at Carnegie Mellon University.

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