Synopsis
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Cutting-edge machine learning principles, practices, and applications
This comprehensive textbook explores the theoretical under¬pinnings 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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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.
"About this title" may belong to another edition of this title.
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Applied Machine Learning
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Applied Machine Learning
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International Edition
Applied Machine Learning
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McGraw-Hill Education, 2019
ISBN 10: 1260456846
ISBN 13: 9781260456844
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Applied Machine Learning
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Applied Machine Learning
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