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Published by American Mathematical Society, 2018
ISBN 10: 1470435756 ISBN 13: 9781470435752
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Published by American Mathematical Society, 2018
ISBN 10: 1470435756 ISBN 13: 9781470435752
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Published by American Mathematical Society, 2018
ISBN 10: 1470435756 ISBN 13: 9781470435752
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ISBN 10: 1470435756 ISBN 13: 9781470435752
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Published by American Mathematical Society, US, 2018
ISBN 10: 1470435756 ISBN 13: 9781470435752
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Hardback. Condition: New. Data science is a highly interdisciplinary field, incorporating ideas from applied mathematics, statistics, probability, and computer science, as well as many other areas. This book gives an introduction to the mathematical methods that form the foundations of machine learning and data science, presented by leading experts in computer science, statistics, and applied mathematics. Although the chapters can be read independently, they are designed to be read together as they lay out algorithmic, statistical, and numerical approaches in diverse but complementary ways.This book can be used both as a text for advanced undergraduate and beginning graduate courses, and as a survey for researchers interested in understanding how applied mathematics broadly defined is being used in data science. It will appeal to anyone interested in the interdisciplinary foundations of machine learning and data science.
Language: English
Published by American Mathematical Society, 2018
ISBN 10: 1470435756 ISBN 13: 9781470435752
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Published by American Mathematical Society, Providence, 2018
ISBN 10: 1470435756 ISBN 13: 9781470435752
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Hardcover. Condition: new. Hardcover. Data science is a highly interdisciplinary field, incorporating ideas from applied mathematics, statistics, probability, and computer science, as well as many other areas. This book gives an introduction to the mathematical methods that form the foundations of machine learning and data science, presented by leading experts in computer science, statistics, and applied mathematics. Although the chapters can be read independently, they are designed to be read together as they lay out algorithmic, statistical, and numerical approaches in diverse but complementary ways.This book can be used both as a text for advanced undergraduate and beginning graduate courses, and as a survey for researchers interested in understanding how applied mathematics broadly defined is being used in data science. It will appeal to anyone interested in the interdisciplinary foundations of machine learning and data science. Data science is a highly interdisciplinary field, incorporating ideas from applied mathematics, statistics, probability, and computer science, as well as many other areas. This book provides an introduction to the mathematical methods that form the foundations of machine learning and data science. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Language: English
Published by Amer Mathematical Society, 2018
ISBN 10: 1470435756 ISBN 13: 9781470435752
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Published by American Mathematical Society, 2018
ISBN 10: 1470435756 ISBN 13: 9781470435752
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Published by American Mathematical Society, 2018
ISBN 10: 1470435756 ISBN 13: 9781470435752
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Published by American Mathematical Society, 2018
ISBN 10: 1470435756 ISBN 13: 9781470435752
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ISBN 10: 1470435756 ISBN 13: 9781470435752
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Published by American Mathematical Society, 2018
ISBN 10: 1470435756 ISBN 13: 9781470435752
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Published by American Mathematical Society, 2018
ISBN 10: 1470435756 ISBN 13: 9781470435752
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Language: English
Published by American Mathematical Society, US, 2018
ISBN 10: 1470435756 ISBN 13: 9781470435752
Seller: Rarewaves.com UK, London, United Kingdom
Hardback. Condition: New. Data science is a highly interdisciplinary field, incorporating ideas from applied mathematics, statistics, probability, and computer science, as well as many other areas. This book gives an introduction to the mathematical methods that form the foundations of machine learning and data science, presented by leading experts in computer science, statistics, and applied mathematics. Although the chapters can be read independently, they are designed to be read together as they lay out algorithmic, statistical, and numerical approaches in diverse but complementary ways.This book can be used both as a text for advanced undergraduate and beginning graduate courses, and as a survey for researchers interested in understanding how applied mathematics broadly defined is being used in data science. It will appeal to anyone interested in the interdisciplinary foundations of machine learning and data science.
Language: English
Published by American Mathematical Society, Providence, 2018
ISBN 10: 1470435756 ISBN 13: 9781470435752
Seller: AussieBookSeller, Truganina, VIC, Australia
Hardcover. Condition: new. Hardcover. Data science is a highly interdisciplinary field, incorporating ideas from applied mathematics, statistics, probability, and computer science, as well as many other areas. This book gives an introduction to the mathematical methods that form the foundations of machine learning and data science, presented by leading experts in computer science, statistics, and applied mathematics. Although the chapters can be read independently, they are designed to be read together as they lay out algorithmic, statistical, and numerical approaches in diverse but complementary ways.This book can be used both as a text for advanced undergraduate and beginning graduate courses, and as a survey for researchers interested in understanding how applied mathematics broadly defined is being used in data science. It will appeal to anyone interested in the interdisciplinary foundations of machine learning and data science. Data science is a highly interdisciplinary field, incorporating ideas from applied mathematics, statistics, probability, and computer science, as well as many other areas. This book provides an introduction to the mathematical methods that form the foundations of machine learning and data science. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.