Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New.
Language: English
Published by Springer Verlag, Singapore, Singapore, 2021
ISBN 10: 9811614377 ISBN 13: 9789811614378
Seller: Grand Eagle Retail, Bensenville, IL, U.S.A.
First Edition
Paperback. Condition: new. Paperback. 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 sparse estimation by considering math problems and building Python programs. Each chapter introduces the notion of sparsity and provides procedures followed by mathematical derivations and source programs with examples of execution. To maximize readers insights into sparsity, mathematical proofs are presented for almost all propositions, and programs are described without depending on any packages. The book is carefully organized to provide the solutions to the exercises in each chapter so that 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 15 lectures (90 mins each). Written in an easy-to-follow and self-contained style, this book will also be perfect material for independent learning by data scientists, machine learning engineers, and researchers interested in linear regression, generalized linear lasso, group lasso, fused lasso, graphical models, matrix decomposition, and multivariate analysis.This book is one of a series of textbooks in machine learning by the same Author. Other titles are: Statistical Learning with Math and R Statistical Learning with Math and Pyth Sparse Estimation with Math and R Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New.
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New.
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition.
Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
Condition: New. Brand New Original US Edition. Customer service! Satisfaction Guaranteed.
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
Condition: New.
Seller: Biblios, Frankfurt am main, HESSE, Germany
Condition: New.
Seller: California Books, Miami, FL, U.S.A.
Condition: New.
Seller: ALLBOOKS1, Direk, SA, Australia
Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
Seller: ALLBOOKS1, Direk, SA, Australia
Brand new book. Fast ship. Please provide full street address as we are not able to ship to P O box address.
Seller: Ria Christie Collections, Uxbridge, United Kingdom
£ 34.30
Quantity: Over 20 available
Add to basketCondition: New. In.
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New.
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: As New. Unread book in perfect condition.
Language: English
Published by Springer-Nature New York Inc, 2021
ISBN 10: 9811614377 ISBN 13: 9789811614378
Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 256 pages. 9.25x6.10x0.61 inches. In Stock.
Language: English
Published by Springer Verlag, Singapore, Singapore, 2021
ISBN 10: 9811614377 ISBN 13: 9789811614378
Seller: AussieBookSeller, Truganina, VIC, Australia
First Edition
Paperback. Condition: new. Paperback. 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 sparse estimation by considering math problems and building Python programs. Each chapter introduces the notion of sparsity and provides procedures followed by mathematical derivations and source programs with examples of execution. To maximize readers insights into sparsity, mathematical proofs are presented for almost all propositions, and programs are described without depending on any packages. The book is carefully organized to provide the solutions to the exercises in each chapter so that 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 15 lectures (90 mins each). Written in an easy-to-follow and self-contained style, this book will also be perfect material for independent learning by data scientists, machine learning engineers, and researchers interested in linear regression, generalized linear lasso, group lasso, fused lasso, graphical models, matrix decomposition, and multivariate analysis.This book is one of a series of textbooks in machine learning by the same Author. Other titles are: Statistical Learning with Math and R Statistical Learning with Math and Pyth Sparse Estimation with Math and R Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Language: English
Published by Springer Nature Singapore, Springer Nature Singapore Okt 2021, 2021
ISBN 10: 9811614377 ISBN 13: 9789811614378
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Taschenbuch. Condition: Neu. 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 sparse estimation by considering math problems and building Python programs.Each chapter introduces the notion of sparsity and provides procedures followed by mathematical derivations and source programs with examples of execution. To maximize readers¿ insights into sparsity, mathematical proofs are presented for almost all propositions, and programs are described without depending on any packages. The book is carefully organized to provide the solutions to the exercises in each chapter so that 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 15 lectures (90 mins each). Written in an easy-to-follow and self-contained style, this book will also be perfect material for independent learning by data scientists, machine learning engineers, and researchers interested in linear regression, generalized linear lasso, group lasso, fused lasso, graphical models, matrix decomposition, and multivariate analysis.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 256 pp. Englisch.
Language: English
Published by Springer Nature Singapore, Springer Nature Singapore, 2021
ISBN 10: 9811614377 ISBN 13: 9789811614378
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering.
Language: English
Published by Springer Nature Singapore Okt 2021, 2021
ISBN 10: 9811614377 ISBN 13: 9789811614378
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 256 pp. Englisch.
Language: English
Published by Springer Nature Singapore, 2021
ISBN 10: 9811614377 ISBN 13: 9789811614378
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 scienceProvides in-depth understanding of source programsWritten in an easy-to-follow and self-contained styleEquips readers with the logic required for machin.
Seller: preigu, Osnabrück, Germany
Taschenbuch. Condition: Neu. Sparse Estimation with Math and Python | 100 Exercises for Building Logic | Joe Suzuki | Taschenbuch | x | Englisch | 2021 | Springer | EAN 9789811614378 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.