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. . . . .

Bestandsnummer des Verk�ufers V9781107057135

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Bibliografische Details

Titel: Understanding Machine Learning: From Theory to Algorithms
Verlag: Cambridge University Press
Ver�ffentlichungsdatum: 2014
Sprache: Englisch
ISBN-10: 1107057132
ISBN-13: 9781107057135
Bindung: Hardcover
Ausgabe: 1. Auflage
Zustand: New

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Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. This book explains the principles behind the automated learning approach and the considerations underlying its usage. The authors explain the 'hows' and 'whys' of machine-learning algorithms, making the field accessible to both students and practitioners.

�ber die Autorinnen und Autoren

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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