Published by Springer, 2020
ISBN 10: 9811575673 ISBN 13: 9789811575679
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ISBN 10: 9811575673 ISBN 13: 9789811575679
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Paperback or Softback. Condition: New. Statistical Learning with Math and R: 100 Exercises for Building Logic 0.73. Book.
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ISBN 10: 9811575673 ISBN 13: 9789811575679
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ISBN 10: 9811575673 ISBN 13: 9789811575679
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Published by Springer, 2020
ISBN 10: 9811575673 ISBN 13: 9789811575679
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ISBN 10: 9811575673 ISBN 13: 9789811575679
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Published by Springer, 2020
ISBN 10: 9811575673 ISBN 13: 9789811575679
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Published by Springer, 2020
ISBN 10: 9811575673 ISBN 13: 9789811575679
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Published by Springer, 2020
ISBN 10: 9811575673 ISBN 13: 9789811575679
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Published by Springer, 2020
ISBN 10: 9811575673 ISBN 13: 9789811575679
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ISBN 10: 9811575673 ISBN 13: 9789811575679
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Published by Springer, 2020
ISBN 10: 9811575673 ISBN 13: 9789811575679
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ISBN 10: 9811575673 ISBN 13: 9789811575679
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ISBN 10: 9811575673 ISBN 13: 9789811575679
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Published by Springer Nature Singapore Okt 2020, 2020
ISBN 10: 9811575673 ISBN 13: 9789811575679
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience. This textbook approaches the essence of machine learning and data science by considering math problems and building R programs.As the preliminary part, Chapter 1 provides a concise introduction to linear algebra, which will help novices read further to the following main chapters. Those succeeding chapters present essential topics in statistical learning: linear regression, classification, resampling, information criteria, regularization, nonlinear regression, decision trees, support vector machines, and unsupervised learning.Each chapter mathematically formulates and solves machine learning problems and builds the programs. The body of a chapter is accompanied by proofs and programs in an appendix, with exercises at the end of the chapter. Because the book is carefully organized to provide the solutions to the exercises in each chapter, readers can solve the total of 100 exercises by simply following the contents of each chapter.This textbook is suitable for an undergraduate or graduate course consisting of about 12 lectures. Written in an easy-to-follow and self-contained style, this book will also be perfect material for independent learning. 232 pp. Englisch.
Published by Springer-Nature New York Inc, 2020
ISBN 10: 9811575673 ISBN 13: 9789811575679
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Published by Springer, 2020
ISBN 10: 9811575673 ISBN 13: 9789811575679
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Published by Springer Verlag, Singapore, 2020
ISBN 10: 9811575673 ISBN 13: 9789811575679
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First Edition
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Published by Springer Nature Singapore, 2020
ISBN 10: 9811575673 ISBN 13: 9789811575679
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience. This textbook approaches the essence of machine learning and data science by considering math problems and building R programs.As the preliminary part, Chapter 1 provides a concise introduction to linear algebra, which will help novices read further to the following main chapters. Those succeeding chapters present essential topics in statistical learning: linear regression, classification, resampling, information criteria, regularization, nonlinear regression, decision trees, support vector machines, and unsupervised learning.Each chapter mathematically formulates and solves machine learning problems and builds the programs. The body of a chapter is accompanied by proofs and programs in an appendix, with exercises at the end of the chapter. Because the book is carefully organized to provide the solutions to the exercisesin each chapter, readers can solve the total of 100 exercises by simply following the contents of each chapter.This textbook is suitable for an undergraduate or graduate course consisting of about 12 lectures. Written in an easy-to-follow and self-contained style, this book will also be perfect material for independent learning.
Published by Springer Verlag, Singapore, 2020
ISBN 10: 9811575673 ISBN 13: 9789811575679
Seller: Kennys Bookstore, Olney, MD, U.S.A.
Condition: New. 2020. 1st ed. 2020. Paperback. . . . . . Books ship from the US and Ireland.
Published by Springer Nature Singapore, 2020
ISBN 10: 9811575673 ISBN 13: 9789811575679
Seller: moluna, Greven, Germany
Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Equips readers with the logic required for machine learning and data science via math and programmingProvides in-depth understanding of R source programs rather than how to use ready-made R packagesWritten in an easy-to-follow and self-cont.
Published by Springer Verlag, 2020
ISBN 10: 9811575673 ISBN 13: 9789811575679
Seller: Collectors Bookstore, Antwerpen, Belgium
Paperback. Condition: Fine. Statistical Learning With Math And R by Joe Suzuki. Published by Springer Verlag in 2020. Paperback ISBN:9789811575679. Collectible item in very fine condition.