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Understanding Machine Learning
SPAR
kr 76
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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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.
Produktdetaljer
Sprog: Engelsk
Sider: 410
ISBN-13: 9781107057135
Indbinding: Hardback
Udgave:
ISBN-10: 1107057132
Kategori: Machine learning
Udg. Dato: 19 maj 2014
Længde: 27mm
Bredde: 186mm
Højde: 261mm
Oplagsdato: 19 maj 2014
Forfatter(e) Shai (University of Waterloo Ben-David, Shai (Hebrew University of Jerusalem) Shalev-Shwartz, Shai Ben-David, Shai Shalev-Shwartz


Kategori Machine learning


Sprog Engelsk


Indbinding Hardback


Sider 410


Udgave


Længde 27mm


Bredde 186mm


Højde 261mm

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