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Understanding Machine Learning : From Theory to Algorithms
Published by Cambridge University Press, 2014
ISBN 10: 1107057132 ISBN 13: 9781107057135
Language: English
Condition: New.
-
Understanding Machine Learning: From Theory To Algorithms
Published by Cambridge University Press CUP, 2014
ISBN 10: 1107057132 ISBN 13: 9781107057135
Language: English
Condition: New. pp. 424 1st edition.
-
Understanding Machine Learning : From Theory to Algorithms
Published by Cambridge University Press, 2014
ISBN 10: 1107057132 ISBN 13: 9781107057135
Language: English
Condition: As New. Unread book in perfect condition.
-
Understanding Machine Learning: From Theory To Algorithms
Published by Cambridge University Press, 2014
ISBN 10: 1107057132 ISBN 13: 9781107057135
Language: English
Condition: New. pp. 424 47 Illus.
-
Understanding Machine Learning : From Theory to Algorithms
Published by Cambridge University Press, 2014
ISBN 10: 1107057132 ISBN 13: 9781107057135
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 77.91
US$ 19.86 shipping from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New.
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Understanding Machine Learning: From Theory To Algorithms
Published by Cambridge University Press, 2014
ISBN 10: 1107057132 ISBN 13: 9781107057135
Language: English
Condition: New. pp. 424.
-
Understanding Machine Learning
Published by Cambridge University Press, GB, 2014
ISBN 10: 1107057132 ISBN 13: 9781107057135
Language: English
Hardback. Condition: New. 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.
-
Understanding Machine Learning : From Theory to Algorithms
Published by Cambridge University Press, 2014
ISBN 10: 1107057132 ISBN 13: 9781107057135
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 88.18
US$ 19.86 shipping from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: As New. Unread book in perfect condition.
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Hardcover. Condition: Brand New. 397 pages. 10.00x7.00x1.00 inches. In Stock.
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Understanding Machine Learning
Published by Cambridge University Press, GB, 2014
ISBN 10: 1107057132 ISBN 13: 9781107057135
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 5 out of 5 stars
Hardback. Condition: New. 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.
-
Understanding Machine Learning
Published by Cambridge University Press, GB, 2014
ISBN 10: 1107057132 ISBN 13: 9781107057135
Language: English
Hardback. Condition: New. 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.
-
Understanding Machine Learning: From Theory to Algorithms
Published by Cambridge University Press, 2014
ISBN 10: 1107057132 ISBN 13: 9781107057135
Language: English
Hardcover. Condition: Like New. Like New. book.
-
Understanding Machine Learning
Published by Cambridge University Press, 2019
ISBN 10: 1107057132 ISBN 13: 9781107057135
Language: English
Condition: Gut. Zustand: Gut | Seiten: 414 | Sprache: Englisch | Produktart: Bücher | 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.
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Understanding Machine Learning
Published by Cambridge University Press, GB, 2014
ISBN 10: 1107057132 ISBN 13: 9781107057135
Language: English
US$ 135.07
US$ 86.06 shipping from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketHardback. Condition: New. 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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Hardcover. Condition: Brand New. 397 pages. 10.00x7.00x1.00 inches. In Stock. This item is printed on demand.
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Understanding Machine Learning
Published by Cambridge University Press, 2016
ISBN 10: 1107057132 ISBN 13: 9781107057135
Language: English
Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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 an.
