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Data Mining and Machine Learning: Fundamental Concepts and Algorithms

Data Mining and Machine Learning: Fundamental Concepts and Algorithms

Data Mining and Machine Learning: Fundamental Concepts and Algorithms
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Data Mining and Machine Learning: Fundamental Concepts and Algorithms Hardback - 2020

by Zaki, Mohammed J.,Meira Jr, Wagner

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Cambridge University Press, 3/12/2020 12:00:01 A. hardcover. Very Good. 1.8504 10.1575 7.2441. Cover and edges may have some wear.
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Details

  • Title Data Mining and Machine Learning: Fundamental Concepts and Algorithms
  • Author Zaki, Mohammed J.,Meira Jr, Wagner
  • Binding Hardback
  • Condition Used - Very good
  • Pages 776
  • Volumes 1
  • Language ENG
  • Publisher Cambridge University Press
  • Publication date 3/12/2020 12:00:01 A
  • Features Bibliography, Index
  • Bookseller's Inventory # mon0004173026
  • ISBN 9781108473989 / 1108473989
  • Weight 3.45 lbs (1.56 kg)
  • Dimensions 9.9 x 6.8 x 1.8 in (25.15 x 17.27 x 4.57 cm)
  • Size 1.8504 10.1575 7.2441
  • Category Computers - Data Base Management
  • Library of Congress subjects Data mining
  • Library of Congress Catalogue Number 2019037293
  • Dewey Decimal Code 006.312
  • Quantity available 4
  • Bookseller catalogues Book

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Reader reviews for Data Mining and Machine Learning: Fundamental Concepts and Algorithms

From the publisher

The fundamental algorithms in data mining and machine learning form the basis of data science, utilizing automated methods to analyze patterns and models for all kinds of data in applications ranging from scientific discovery to business analytics. This textbook for senior undergraduate and graduate courses provides a comprehensive, in-depth overview of data mining, machine learning and statistics, offering solid guidance for students, researchers, and practitioners. The book lays the foundations of data analysis, pattern mining, clustering, classification and regression, with a focus on the algorithms and the underlying algebraic, geometric, and probabilistic concepts. New to this second edition is an entire part devoted to regression methods, including neural networks and deep learning.
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