Autor: Shai Shalev-Shwartz , Shai Ben-David
Wydawca: Cambridge University Press
Dostępność: 3-6 tygodni
Cena: 307,65 zł
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ISBN13: |
9781107057135 |
ISBN10: |
1107057132 |
Autor: |
Shai Shalev-Shwartz , Shai Ben-David |
Oprawa: |
Hardback |
Rok Wydania: |
2014-07-17 |
Ilość stron: |
410 |
Wymiary: |
253 x 177 mm |
Tematy: |
Pattern recognition |
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 a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics, the book covers a wide array of central topics unaddressed by previous textbooks. These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for advanced undergraduates or beginning graduates, the text makes the fundamentals and algorithms of machine learning accessible to students and non-expert readers in statistics, computer science, mathematics and engineering.
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