Applied Machine Learning

Applied Machine Learning Front Cover
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656 pages

Book Description

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Cutting-edge principles, practices, and applications

This comprehensive textbook explores the theoretical underĀ¬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 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 (NN)
  • Fuzzy inference
  • Data clustering
  • Data transformations
  • Decision tree learning
  • And much more

Book Details

  • Title: Applied Machine Learning
  • Author:
  • Length: 656 pages
  • Edition: 1
  • Language: English
  • Publisher:
  • Publication Date: 2019-06-05
  • ISBN-10: 1260456846
  • ISBN-13: 9781260456844
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