Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage. Num Pages: 409 pages, 47 b/w illus. 123 exercises. BIC Classification: UYQM. Category: (U) Tertiary Education (US: College). Dimension: 186 x 261 x 29. Weight in Grams: 912. . 2014. 1st Edition. Hardcover. . . . .

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Bibliographic Details

Title: Understanding Machine Learning: From Theory to Algorithms
Publisher: Cambridge University Press
Publication Date: 2014
Language: English
ISBN 10: 1107057132
ISBN 13: 9781107057135
Binding: Hardcover
Edition: 1st Edition
Condition: New

About this title

Synopsis

Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.

About the Authors

Shai Shalev-Shwartz is an Associate Professor at the School of Computer Science and Engineering at the Hebrew University of Jerusalem, Israel.

Shai Ben-David is a Professor in the School of Computer Science at the University of Waterloo, Canada.

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