Applied Machine Learning
Language: English
Published by McGraw-Hill Education, 2019
- Hardcover
- Used
Seller: World of Books (was SecondSale), Montgomery, IL, U.S.A.World of Books (was SecondSale)
AbeBooks seller since December 20, 2007
Condition: Used - Good
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Add to basketItem description from seller
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 applicationsThis 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.…
Seller Inventory # 00110741448
- Title
- Applied Machine Learning
- Author
- M Gopal
- Publisher
- McGraw-Hill Education
- Publication year
- 2019
- Condition
- Good
- Binding
- Hardback
- Language
- English
- ISBN 10
- 1260456846
- ISBN 13
- 9781260456844
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
"About the title" may belong to another edition of this title.
World of Books (was SecondSale)
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