Learning from Data: Concepts, Theory, and Methods Second Edition
Cherkassky, Vladimir, Mulier, Filip M.
ISBN 10: 0471681822 ISBN 13: 9780471681823
Published by Wiley-IEEE Press, 2007
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*Price HAS BEEN REDUCED by 10% until Monday, June 23. Order now for BEST SAVINGS* 2nd edition, 560 pp., hardcover, previous owner's name neatly inked to the title page, else fine. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country. Seller Inventory # ZB1317152
Synopsis:
An interdisciplinary framework for learning methodologies―covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied―showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text.
About the Author:
Vladimir CherKassky, PhD, is Professor of Electrical and Computer Engineering at the University of Minnesota. He is internationally known for his research on neural networks and statistical learning.
Filip Mulier, PhD, has worked in the software field for the last twelve years, part of which has been spent researching, developing, and applying advanced statistical and machine learning methods. He currently holds a project management position.
"About this title" may belong to another edition of this title.
Bibliographic Details
Title: Learning from Data: Concepts, Theory, and ...
Publisher: Wiley-IEEE Press
Publication Date: 2007
Binding: Hardcover
Condition: Fine
Edition: 2nd Edition
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Learning from Data: Concepts, Theory, and Methods
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Learning from Data: Concepts, Theory, and Methods
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ISBN 10: 0471681822
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Learning from Data: Concepts, Theory, and Methods (IEEE Press)
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Learning from Data (Hardcover)
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Hardcover. Condition: new. Hardcover. An interdisciplinary framework for learning methodologiescovering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be appliedshowing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text. An interdisciplinary framework for learning methodologies, covering statistics, neural networks, and fuzzy logic, Learning from Data provides a unified treatment of the principles and methods for learning dependencies from data. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780471681823
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Learning from Data
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Learning from Data
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Gebunden. Condition: New. Vladimir CherKassky, PhD, is Professor of Electrical and Computer Engineering at the University of Minnesota. He is internationally known for his research on neural networks and statistical learning.Filip Mulier, PhD, has worked in the software field for th. Seller Inventory # 446917716
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Learning from Data (Hardcover)
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ISBN 10: 0471681822
ISBN 13: 9780471681823
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Hardcover. Condition: new. Hardcover. An interdisciplinary framework for learning methodologiescovering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be appliedshowing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text. An interdisciplinary framework for learning methodologies, covering statistics, neural networks, and fuzzy logic, Learning from Data provides a unified treatment of the principles and methods for learning dependencies from data. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9780471681823
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