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    Foundations of Machine Learning (Adaptive Computation and Machine Learning) (Hardback) By (author) Mehryar Mohri, By (author) Afshin Rostamizadeh, By (author) Ameet Talwalkar

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    DescriptionThis 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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  • Full bibliographic data for Foundations of Machine Learning

    Foundations of Machine Learning
    Authors and contributors
    By (author) Mehryar Mohri, By (author) Afshin Rostamizadeh, By (author) Ameet Talwalkar
    Physical properties
    Format: Hardback
    Number of pages: 432
    Width: 178 mm
    Height: 229 mm
    Thickness: 28 mm
    Weight: 1,111 g
    ISBN 13: 9780262018258
    ISBN 10: 026201825X

    BIC E4L: COM
    B&T Book Type: NF
    B&T Modifier: Region of Publication: 01
    Nielsen BookScan Product Class 3: S10.3T
    Warengruppen-Systematik des deutschen Buchhandels: 16320
    B&T Modifier: Academic Level: 02
    B&T Modifier: Text Format: 06
    B&T General Subject: 229
    B&T Modifier: Text Format: 01
    LC subject heading: ,
    B&T Merchandise Category: COM
    Ingram Subject Code: XG
    Libri: I-XG
    LC subject heading:
    DC22: 006.3/1
    LC subject heading:
    DC22: 006.31
    BIC subject category V2: UYQM
    BISAC V2.8: COM037000
    DC23: 006.31
    LC classification: Q325.5 .M64 2012
    Thema V1.0: UYQM
    Illustrations note
    55 color illus., 40 b&w illus.
    MIT Press Ltd
    Imprint name
    MIT Press
    Publication date
    07 September 2012
    Publication City/Country
    Cambridge, Mass.
    Author 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 a National Science Foundation Postdoctoral Fellow in the Department of Electrical Engineering and Computer Science at the University of California, Berkeley.
    Review quote
    "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 commentsprovided 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