Understanding machine learning : from theory to algorithms / Shai Shalev-Shwartz, Shai Ben-David.
Material type:
TextLanguage: English Publication details: New York, NY, USA : Cambridge University Press, 2014Description: xvi, 397 pages : illustrations (black and white) ; 27 cmISBN: - 9781107057135
- 9781107512825
- 006.31 23 SHA
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General Books
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CUTN Central Library Generalia | Non-fiction | 006.31 SHA (Browse shelf(Opens below)) | Available | 36788 |
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| 006.31 RAS Machine learning with Pytorch and Scikit-learn : develop machine learning and deep learning models with Python / | 006.31 ROG A first course in machine learning / | 006.31 SEJ The deep learning revolution / | 006.31 SHA Understanding machine learning : | 006.31 SRA Optimization for machine learning / | 006.31 SRA Optimization for machine learning / | 006.31 SRA Optimization for machine learning / |
PART I:Foundations PART II:From Theory to Algorithms PART III:Additional Learning Models PART IV:Advanced Theory
"Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations that transform these principles into practical Read more...
Includes bibliographical references and index.
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