Understanding Machine Learning: From Theory to Algorithms

Shai Shalev-Shwartz

ISBN 10: 1107057132 / ISBN 13: 9781107057135

Verlag: Cambridge University Press, 2014

Beschreibung

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. . . . . Books ship from the US and Ireland.

Bestandsnummer des Verkäufers V9781107057135

Bibliografische Details

• Titel: Understanding Machine Learning: From Theory to Algorithms
• Verlag: Cambridge University Press
• Veröffentlichungsdatum: 2014
• Sprache: Englisch
• ISBN-10: 1107057132
• ISBN-13: 9781107057135
• Bindung: Hardcover
• Zustand: New

Über diesen Titel

Inhaltsangabe

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.

Über 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.