Foundations of Machine Learning (Adaptive Computation and Machine Learning series)

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( 41 valoraciones por Goodreads )
 
9780262018258: Foundations of Machine Learning (Adaptive Computation and Machine Learning series)

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

About the Author:

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:

A solid, comprehensive, and self-contained book providing a uniform treatment of a very broad collection of machine learning algorithms and problems. Foundations of Machine Learning is an essential reference book for corporate and academic researchers, engineers, and students.

(Corinna Cortes, Head of Google Research, NY)

Finally, a book that is both broad enough to cover many algorithmic topics of machine learning and mathematically deep enough to introduce the required theory for a graduate level course. Foundations of Machine Learning is a great achievement and a significant contribution to the machine learning community.

(Yishay Mansour, School of Computer Science, Tel Aviv University)

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)

"Sobre este título" puede pertenecer a otra edición de este libro.

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Mohri, Mehryar; Rostamizadeh, Afshin; Talwalkar, Ameet
Editorial: MIT Press Ltd (2012)
ISBN 10: 026201825X ISBN 13: 9780262018258
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Descripción MIT Press Ltd, 2012. Estado de conservación: New. 2012. Hardcover. Series: Adaptive Computation and Machine Learning Series. Num Pages: 432 pages, 55 color illus., 40 b&w illus. BIC Classification: UYQM. Category: (G) General (US: Trade). Dimension: 235 x 178 x 28. Weight in Grams: 1104. . . . . . . Nº de ref. de la librería V9780262018258

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Mohri, Mehryar
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Descripción MIT Press, 2012. HRD. Estado de conservación: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Nº de ref. de la librería BB-9780262018258

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Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar
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ISBN 10: 026201825X ISBN 13: 9780262018258
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Descripción MIT Press Ltd, United States, 2012. Hardback. Estado de conservación: New. Language: English . Brand New Book. 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. Nº de ref. de la librería AAU9780262018258

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Descripción MIT Press. Hardcover. Estado de conservación: New. New copy - Usually dispatched within 2 working days. Nº de ref. de la librería B9780262018258

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Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar
Editorial: MIT Press Ltd, United States (2012)
ISBN 10: 026201825X ISBN 13: 9780262018258
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Descripción MIT Press Ltd, United States, 2012. Hardback. Estado de conservación: New. Language: English . Brand New Book. 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. Nº de ref. de la librería AAU9780262018258

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Mohri, Mehryar; Rostamizadeh, Afshin; Talwalkar, Ameet
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Descripción MIT Press Ltd. Estado de conservación: New. 2012. Hardcover. Series: Adaptive Computation and Machine Learning Series. Num Pages: 432 pages, 55 color illus., 40 b&w illus. BIC Classification: UYQM. Category: (G) General (US: Trade). Dimension: 235 x 178 x 28. Weight in Grams: 1104. . . . . . Books ship from the US and Ireland. Nº de ref. de la librería V9780262018258

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Mehryar Mohri, Afshin Rostamizadeh, Ameet Talwalkar
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Descripción MIT Press 2012-09-07, Cambridge, MA, 2012. hardback. Estado de conservación: New. Nº de ref. de la librería 9780262018258

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Descripción MIT Press 2012-09-07, 2012. Estado de conservación: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely. Nº de ref. de la librería NU-GRD-04896955

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Mehryar Mohri; Afshin Rostamizadeh; Ameet Talwalkar
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Mehryar Mohri
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Descripción Mit University Press Group Ltd, 2012. Estado de conservación: New. Nº de ref. de la librería EH9780262018258

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