Published by Cambridge University Press (edition New), 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
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Published by Cambridge University Press, 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
Language: English
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Add to basketpaperback. Condition: Very Good. Machine Learning Fundamentals: A Concise Introduction This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .
Published by Cambridge University Press, 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
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Published by Cambridge University Press, 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
Language: English
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Published by Cambridge University Press -, 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
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Published by Cambridge University Press, 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
Language: English
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Published by Cambridge University Press, 2022
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Published by Cambridge University Press, 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
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Published by Cambridge University Press, 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
Language: English
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Published by Cambridge University Press, 2021
ISBN 10: 1108940021 ISBN 13: 9781108940023
Language: English
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Published by Cambridge University Press, 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
Language: English
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Published by Cambridge University Press, Cambridge, 2021
ISBN 10: 1108940021 ISBN 13: 9781108940023
Language: English
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Paperback. Condition: new. Paperback. This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely from scratch based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts. This lucid and coherent introduction to supervised machine learning presents core concepts in a concise, logical and easy-to-follow way for readers with some mathematical preparation but no prior exposure to machine learning. Coverage includes widely used traditional methods plus recently popular deep learning methods. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Published by Cambridge University Press CUP, 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
Language: English
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Published by Cambridge University Press, 2021
ISBN 10: 1108940021 ISBN 13: 9781108940023
Language: English
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Published by Cambridge University Press, 2022
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Published by Cambridge University Press, 2022
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Published by Cambridge University Press, 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
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Published by Cambridge University Press, 2021
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Published by Cambridge University Press, 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
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Published by Cambridge University Press, 2022
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Published by Cambridge University Press, 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
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Published by Cambridge University Press, 2021
ISBN 10: 1108940021 ISBN 13: 9781108940023
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Published by Cambridge University Press Mär 2022, 2022
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Add to basketTaschenbuch. Condition: Neu. Neuware - A coherent introduction to core concepts and deep learning techniques that are critical to academic research and real-world applications.
Published by Cambridge University Press, 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
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Published by Cambridge University Press Academic (11/2021), 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
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Published by Cambridge University Press, Cambridge, 2021
ISBN 10: 1108940021 ISBN 13: 9781108940023
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Add to basketPaperback. Condition: new. Paperback. This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely from scratch based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts. This lucid and coherent introduction to supervised machine learning presents core concepts in a concise, logical and easy-to-follow way for readers with some mathematical preparation but no prior exposure to machine learning. Coverage includes widely used traditional methods plus recently popular deep learning methods. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Published by Cambridge University Pr., 2022
ISBN 10: 1108940021 ISBN 13: 9781108940023
Language: English
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Add to basketCondition: New. This lucid and coherent introduction to supervised machine learning presents core concepts in a concise, logical and easy-to-follow way for readers with some mathematical preparation but no prior exposure to machine learning. Coverage includes widely used t.
Published by Cambridge University Press, Cambridge, 2021
ISBN 10: 1108940021 ISBN 13: 9781108940023
Language: English
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Add to basketPaperback. Condition: new. Paperback. This lucid, accessible introduction to supervised machine learning presents core concepts in a focused and logical way that is easy for beginners to follow. The author assumes basic calculus, linear algebra, probability and statistics but no prior exposure to machine learning. Coverage includes widely used traditional methods such as SVMs, boosted trees, HMMs, and LDAs, plus popular deep learning methods such as convolution neural nets, attention, transformers, and GANs. Organized in a coherent presentation framework that emphasizes the big picture, the text introduces each method clearly and concisely from scratch based on the fundamentals. All methods and algorithms are described by a clean and consistent style, with a minimum of unnecessary detail. Numerous case studies and concrete examples demonstrate how the methods can be applied in a variety of contexts. This lucid and coherent introduction to supervised machine learning presents core concepts in a concise, logical and easy-to-follow way for readers with some mathematical preparation but no prior exposure to machine learning. Coverage includes widely used traditional methods plus recently popular deep learning methods. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.