Applied machine learning By M.Gopal.

By:

Gopal, M

Material type: Text

TextPublication details: India; McGraw Hill Education India, c2022.Edition: 2nd EdDescription: i-xx+526PISBN:

9789354601590

Subject(s):

Machine learning -- Textbooks. Mechanical engineering -- Textbooks

DDC classification:

006.31 GOP-A

Contents:

Introduction -- Supervised learning: rationale and basics -- Statistical learning -- Learning with Support Vector Machines (SVM) -- Learning with Neural Networks (NN) -- Fuzzy inference systems -- Data clustering and data transformations -- Decision tree learning -- Business intelligence and data mining : techniques and applications -- Appendix A: Genetic Algorithm (GA) for search optimization -- Appendix B: Reinforcement Learning (RL) -- Datasets from real-life applications for machine learning experiments -- Problems.

Summary: "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, acurately represent data, select and tune algorithms, interpret and analyze results, and make informed strategic decisions. Presented in a non-rigorous mathematical syle, the book covers a broad array of machine learning ropics with special emphasis on methods that have been profitably employed." -- back cover.

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Holdings
Item type	Current library	Home library	Call number	Status	Date due	Barcode
Book	Dept. of Computational Biology and Bioinformatics Processing Center	Dept. of Computational Biology and Bioinformatics	006.31 GOP-A (Browse shelf(Opens below))	Available		DCB4100

Introduction --
Supervised learning: rationale and basics --
Statistical learning --
Learning with Support Vector Machines (SVM) --
Learning with Neural Networks (NN) --
Fuzzy inference systems --
Data clustering and data transformations --
Decision tree learning --
Business intelligence and data mining : techniques and applications --
Appendix A: Genetic Algorithm (GA) for search optimization --
Appendix B: Reinforcement Learning (RL) --
Datasets from real-life applications for machine learning experiments --
Problems.

"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, acurately represent data, select and tune algorithms, interpret and analyze results, and make informed strategic decisions. Presented in a non-rigorous mathematical syle, the book covers a broad array of machine learning ropics with special emphasis on methods that have been profitably employed." -- back cover.

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