Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: HPB-Red, Dallas, TX, U.S.A.
EUR 38,29
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Aggiungi al carrellohardcover. Condizione: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
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Aggiungi al carrelloSoft cover. Condizione: New. This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counter-intuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. In addition, important structural and complexity measures, such as matrix norms and VC-dimension, are discussed. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data. This beautifully written text is a scholarly journey through the mathematical and algorithmic foundations of data science. Rigorous but accessible, and with many exercises, it will be a valuable resource for advanced undergraduate and graduate classes. Peter Bartlett, University of California, Berkeley. A lucid account of mathematical ideas that underlie today's data analysis and machine learning methods. I learnt a lot from it, and I am sure it will become an invaluable reference for many students, researchers and faculty around the world. Sanjeev Arora, Princeton University, New Jersey.
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: Better World Books, Mishawaka, IN, U.S.A.
EUR 52,93
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Aggiungi al carrelloCondizione: Very Good. Former library book; may include library markings. Used book that is in excellent condition. May show signs of wear or have minor defects.
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 57,30
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Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: Lucky's Textbooks, Dallas, TX, U.S.A.
EUR 56,10
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Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: California Books, Miami, FL, U.S.A.
EUR 63,23
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Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: GreatBookPrices, Columbia, MD, U.S.A.
EUR 65,09
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Editore: Cambridge University Press, Cambridge, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.
EUR 69,06
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data. This book is aimed towards both undergraduate and graduate courses in computer science on the design and analysis of algorithms for data. The material in this book will provide students with the mathematical background they need for further study and research in machine learning, data mining, and data science more generally. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: Ria Christie Collections, Uxbridge, Regno Unito
EUR 60,58
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Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: Majestic Books, Hounslow, Regno Unito
EUR 68,81
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Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 60,57
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Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlanda
EUR 68,73
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Editore: Cambridge University Press CUP, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: Books Puddle, New York, NY, U.S.A.
EUR 79,22
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Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: GreatBookPricesUK, Woodford Green, Regno Unito
EUR 68,66
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Aggiungi al carrelloCondizione: As New. Unread book in perfect condition.
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: Kennys Bookstore, Olney, MD, U.S.A.
EUR 85,23
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Aggiungi al carrelloCondizione: New. 2020. Hardcover. . . . . . Books ship from the US and Ireland.
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: Biblios, Frankfurt am main, HESSE, Germania
EUR 82,96
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Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: Speedyhen, London, Regno Unito
EUR 53,62
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Editore: Cambridge University Press, Cambridge, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: CitiRetail, Stevenage, Regno Unito
EUR 67,52
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data. This book is aimed towards both undergraduate and graduate courses in computer science on the design and analysis of algorithms for data. The material in this book will provide students with the mathematical background they need for further study and research in machine learning, data mining, and data science more generally. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
EUR 87,31
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Aggiungi al carrelloHardcover. Condizione: Brand New. 424 pages. 10.25x7.25x1.00 inches. In Stock.
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: moluna, Greven, Germania
EUR 66,08
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Aggiungi al carrelloCondizione: New. This book is aimed towards both undergraduate and graduate courses in computer science on the design and analysis of algorithms for data. The material in this book will provide students with the mathematical background they need for further study and resear.
Editore: Cambridge University Press, Cambridge, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: AussieBookSeller, Truganina, VIC, Australia
EUR 88,53
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Aggiungi al carrelloHardcover. Condizione: new. Hardcover. This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data. This book is aimed towards both undergraduate and graduate courses in computer science on the design and analysis of algorithms for data. The material in this book will provide students with the mathematical background they need for further study and research in machine learning, data mining, and data science more generally. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: Mispah books, Redhill, SURRE, Regno Unito
EUR 91,22
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Aggiungi al carrelloHardcover. Condizione: New. New. book.
Editore: Cambridge University Press, 2020
ISBN 10: 1108485065 ISBN 13: 9781108485067
Lingua: Inglese
Da: AHA-BUCH GmbH, Einbeck, Germania
EUR 69,56
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Aggiungi al carrelloBuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is aimed towards both undergraduate and graduate courses in computer science on the design and analysis of algorithms for data. The material in this book will provide students with the mathematical background they need for further study and research in machine learning, data mining, and data science more generally.
Da: Revaluation Books, Exeter, Regno Unito
EUR 62,25
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Aggiungi al carrelloHardcover. Condizione: Brand New. 424 pages. 10.25x7.25x1.00 inches. In Stock. This item is printed on demand.