Published by Cambridge University Press, 2016
ISBN 10: 1107123526 ISBN 13: 9781107123526
Language: English
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Published by Cambridge University Press, 2016
ISBN 10: 1107123526 ISBN 13: 9781107123526
Language: English
Seller: Bay State Book Company, North Smithfield, RI, U.S.A.
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Published by Cambridge University Press, 2016
ISBN 10: 1107123526 ISBN 13: 9781107123526
Language: English
Seller: Books From California, Simi Valley, CA, U.S.A.
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Published by Cambridge University Press (edition 2), 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
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Published by Cambridge University Press, 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
Seller: Books From California, Simi Valley, CA, U.S.A.
hardcover. Condition: Very Good.
Published by Cambridge University Press, 2016
ISBN 10: 1107123526 ISBN 13: 9781107123526
Language: English
Seller: Books From California, Simi Valley, CA, U.S.A.
hardcover. Condition: Fine.
Published by Cambridge University Press, 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
Seller: SecondSale, Montgomery, IL, U.S.A.
Condition: Good. Item in good condition. Textbooks may not include supplemental items i.e. CDs, access codes etc.
Published by Cambridge University Press (edition 2), 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
Seller: BooksRun, Philadelphia, PA, U.S.A.
Hardcover. Condition: Very Good. 2. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
Published by Cambridge University Press, 2016
ISBN 10: 1107123526 ISBN 13: 9781107123526
Language: English
Seller: Labyrinth Books, Princeton, NJ, U.S.A.
Condition: Very Good.
Published by Cambridge University Press
Seller: Academic Book Solutions, Medford, NY, U.S.A.
hardcover. Condition: LikeNew. Used Like New, no missing pages, no damage to binding, may have a remainder mark.
Published by Cambridge University Press, 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition.
Published by Cambridge University Press, 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New.
Published by Cambridge University Press, 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
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Published by Cambridge University Press, 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
Seller: AMM Books, Gillingham, KENT, United Kingdom
£ 50.19
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Published by Cambridge University Press, 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
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Published by Cambridge University Press, 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
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Published by Cambridge University Press, 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
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£ 64.14
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Published by Cambridge University Press, 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
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Published by Cambridge University Press, GB, 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
Seller: Rarewaves USA, OSWEGO, IL, U.S.A.
Hardback. Condition: New. With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in Python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for graduate courses on machine learning and for individual reference and self-study.
Seller: Revaluation Books, Exeter, United Kingdom
£ 68.14
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Add to basketHardcover. Condition: Brand New. 2nd edition. 574 pages. 9.75x6.75x1.25 inches. In Stock.
Seller: Revaluation Books, Exeter, United Kingdom
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Add to basketHardcover. Condition: Brand New. 1st edition. 298 pages. 10.00x7.00x0.50 inches. In Stock.
Published by Cambridge University Press, GB, 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
£ 108.99
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Add to basketHardback. Condition: New. With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in Python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for graduate courses on machine learning and for individual reference and self-study.
Published by Cambridge University Press, 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
Seller: moluna, Greven, Germany
£ 73.81
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Add to basketCondition: New. An intuitive approach to machine learning detailing the key concepts needed to build products and conduct research. Featuring color illustrations, real-world examples, practical coding exercises, and an online package including sample code, data sets, lectu.
Seller: Revaluation Books, Exeter, United Kingdom
£ 101.38
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Add to basketHardcover. Condition: Brand New. 2nd edition. 574 pages. 9.75x6.75x1.25 inches. In Stock.
Published by Cambridge University Press, GB, 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
Seller: Rarewaves USA United, OSWEGO, IL, U.S.A.
Hardback. Condition: New. With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in Python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for graduate courses on machine learning and for individual reference and self-study.
Published by Cambridge University Press, GB, 2020
ISBN 10: 1108480721 ISBN 13: 9781108480727
Language: English
Seller: Rarewaves.com UK, London, United Kingdom
£ 99.81
Convert currencyQuantity: 2 available
Add to basketHardback. Condition: New. With its intuitive yet rigorous approach to machine learning, this text provides students with the fundamental knowledge and practical tools needed to conduct research and build data-driven products. The authors prioritize geometric intuition and algorithmic thinking, and include detail on all the essential mathematical prerequisites, to offer a fresh and accessible way to learn. Practical applications are emphasized, with examples from disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology. Over 300 color illustrations are included and have been meticulously designed to enable an intuitive grasp of technical concepts, and over 100 in-depth coding exercises (in Python) provide a real understanding of crucial machine learning algorithms. A suite of online resources including sample code, data sets, interactive lecture slides, and a solutions manual are provided online, making this an ideal text both for graduate courses on machine learning and for individual reference and self-study.