Applied machine learning M. Gopal

By:

Gopal, M [author.]

Material type: Text

TextPublication details: United States of America : McGraw-Hill Education , 2019.Description: xix, 630 pages : figures, tables ; 27 cmContent type:

text

Media type:

unmediated

Carrier type:

volume

ISBN:

9781260456844

DDC classification:

006.31 G646a

Summary: Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Cutting-edge machine learning principles, practices, and applications This comprehensive textbook explores the theoretical underƠpinnings of learning and equips readers with the knowledge needed to apply powerful machine learning techniques to solve challenging real-world problems. Applied Machine Learning shows, step by step, how to conceptualize problems, accurately represent data, select and tune algorithms, interpret and analyze results, and make informed strategic decisions. Presented in a non-rigorous mathematical style, the book covers a broad array of machine learning topics with special emphasis on methods that have been profitably employed. Coverage includes: •Supervised learning •Statistical learning •Learning with support vector machines (SVM) •Learning with neural networks (NN) •Fuzzy inference systems •Data clustering •Data transformations •Decision tree learning •Business intelligence •Data mining •And much more

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Holdings
Item type	Current library	Shelving location	Call number	Copy number	Status	Date due	Barcode
Books	Main Library	Engineering Section	ENG 006.31 G646a 2019 (Browse shelf(Opens below))	1-2	Available		023618
Books	Main Library	Engineering Section	ENG 006.31 G646a 2019 (Browse shelf(Opens below))	2-2	Available		023619

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Includes index,

Includes bibliographical references pages (613-622).

Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Cutting-edge machine learning principles, practices, and applications This comprehensive textbook explores the theoretical underƠpinnings of learning and equips readers with the knowledge needed to apply powerful machine learning techniques to solve challenging real-world problems. Applied Machine Learning shows, step by step, how to conceptualize problems, accurately represent data, select and tune algorithms, interpret and analyze results, and make informed strategic decisions. Presented in a non-rigorous mathematical style, the book covers a broad array of machine learning topics with special emphasis on methods that have been profitably employed. Coverage includes: •Supervised learning •Statistical learning •Learning with support vector machines (SVM) •Learning with neural networks (NN) •Fuzzy inference systems •Data clustering •Data transformations •Decision tree learning •Business intelligence •Data mining •And much more

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