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Introduction to Statistical Machine Learning

Introduction to Statistical Machine Learning

Introduction to Statistical Machine Learning
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Introduction to Statistical Machine Learning Papeback -

by Masashi Sugiyama

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Elsevier , pp. 624 . Papeback. New.
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Details

  • Title Introduction to Statistical Machine Learning
  • Author Masashi Sugiyama
  • Binding Papeback
  • Edition Paperback
  • Condition New
  • Pages 534
  • Volumes 1
  • Language ENG
  • Publisher Elsevier
  • Publication date pp. 624
  • Features Bibliography, Index
  • Bookseller's Inventory # 6372648629
  • ISBN 9780128021217 / 0128021217
  • Weight 2.4 lbs (1.09 kg)
  • Dimensions 9.2 x 7.5 x 1 in (23.37 x 19.05 x 2.54 cm)
  • Category Computers - General Information
  • Library of Congress subjects Machine learning - Statistical methods, Aprendizaje automaatico (Inteligencia
  • Library of Congress Catalogue Number 2016498470
  • Dewey Decimal Code 006.31
  • Quantity available 3

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Reader reviews for Introduction to Statistical Machine Learning

From the publisher

Machine learning allows computers to learn and discern patterns without actually being programmed. When Statistical techniques and machine learning are combined together they are a powerful tool for analysing various kinds of data in many computer science/engineering areas including, image processing, speech processing, natural language processing, robot control, as well as in fundamental sciences such as biology, medicine, astronomy, physics, and materials.

Introduction to Statistical Machine Learning provides a general introduction to machine learning that covers a wide range of topics concisely and will help you bridge the gap between theory and practice. Part I discusses the fundamental concepts of statistics and probability that are used in describing machine learning algorithms. Part II and Part III explain the two major approaches of machine learning techniques; generative methods and discriminative methods. While Part III provides an in-depth look at advanced topics that play essential roles in making machine learning algorithms more useful in practice. The accompanying MATLAB/Octave programs provide you with the necessary practical skills needed to accomplish a wide range of data analysis tasks.

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