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Applied Machine Learning

Applied Machine Learning

Applied Machine Learning
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Applied Machine Learning Hardback - 2019

by Gopal, M

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Description

McGraw-Hill, 2019. Hardcover. New. 630 pages. 10.50x8.25x1.50 inches.
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Details

  • Title Applied Machine Learning
  • Author Gopal, M
  • Binding Hardback
  • Condition New
  • Pages 656
  • Volumes 1
  • Language ENG
  • Publisher McGraw-Hill
  • Publication date 2019
  • Illustrated Yes
  • Bookseller's Inventory # 2-1260456846
  • ISBN 9781260456844 / 1260456846
  • Weight 3.29 lbs (1.49 kg)
  • Dimensions 10.3 x 8 x 1.52 in (26.16 x 20.32 x 3.86 cm)
  • Category Technology & Industrial Arts
  • Library of Congress subjects Machine learning, Mechanical engineering
  • Library of Congress Catalogue Number 2018966932
  • Dewey Decimal Code 006.31
  • Quantity available 1

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Reader reviews for Applied Machine Learning

From the publisher

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 underpinnings 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

About the author

M. Gopal, is a former professor of IIT Delhi, is a globally known academician with excellent credentials as an author, teacher, and researcher. He is the author or co-author of five books on control engineering.
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