9781107057135 - understanding machine learning: from theory to algorithms de shalev-shwartz, shai (34 resultados)
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Librería: Readify Books, New Castle, DE, Estados Unidos de AmericaReadify Books
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Paperback. Condición: NEW. International Edition, Paperback, Brand New,ISBN and Cover image may differ but contents similar to U.S. Edition. We ship from multiple Locations including India, We ship to PO , APO and FPO adresses in U.S.A. Choose Expedited Shipping for FASTER DELIVERY.Customer Satisfaction Guaranteed.
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hardcover. Condición: New. 1st Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).
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Condición: Good. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In good all round condition. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,1000grams, ISBN:9781107057135.
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Condición: New. pp. 424 1st edition.
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Condición: New. pp. 424 47 Illus.
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Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios
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Condición: New. pp. 424.
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Librería: Chiron Media, Wallingford, , Reino UnidoChiron Media
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Hardcover. Condición: new. Hardcover. 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 under…lying 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. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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EUR 72,02
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Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA
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Hardback. Condición: 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 machin…e 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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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, , AlemaniaBuchWeltWeit Ludwig Meier e.K.
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EUR 67,60
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Buch. Condición: Neu. Neuware -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 m…achine 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. 414 pp. Englisch.
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Librería: Rheinberg-Buch Andreas Meier eK, Bergisch Gladbach, , AlemaniaRheinberg-Buch Andreas Meier eK
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EUR 67,60
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Buch. Condición: Neu. Neuware -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 m…achine 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. 414 pp. Englisch.
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Librería: Kennys Bookshop and Art Galleries Ltd., Galway, GY, IrlandaKennys Bookshop and Art Galleries Ltd.
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EUR 83,59
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Condición: New. 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. . . . .
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Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK
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Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA
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EUR 101,05
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Hardback. Condición: 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 machin…e 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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Librería: Kennys Bookstore, Olney, MD, Estados Unidos de AmericaKennys Bookstore
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EUR 104,04
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Condición: New. 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.
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Librería: moluna, Greven, , Alemaniamoluna
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EUR 66,41
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Gebunden. Condición: New. 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.
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Librería: Revaluation Books, Exeter, , Reino UnidoRevaluation Books
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Hardcover. Condición: Brand New. 397 pages. 10.00x7.00x1.00 inches. In Stock.
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Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de AmericaRarewaves USA United
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EUR 92,24
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Hardback. Condición: 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 machin…e 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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Librería: preigu, Osnabrück, Alemaniapreigu
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EUR 62,55
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Buch. Condición: Neu. Understanding Machine Learning | Shai Shalev-Shwartz (u. a.) | Buch | Geb gebundene Bücher | Englisch | 2019 | Cambridge University Press | EAN 9781107057135 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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EUR 111,11
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Hardcover. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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EUR 76,68
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Buch. Condición: Neu. Neuware - 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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Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 131,66
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Hardcover. Condición: new. Hardcover. 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 under…lying 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. 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. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
