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The Machine Learning - (Adaptive Computation and Machine Learning) by Kevin P Murphy (Hardcover)

The Machine Learning - (Adaptive Computation and Machine Learning) by  Kevin P Murphy (Hardcover) - 1 of 1
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About this item

Highlights

  • A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.Today's Web-enabled deluge of electronic data calls for automated methods of data analysis.
  • About the Author: Kevin P. Murphy is a Senior Staff Research Scientist at Google Research.
  • 1104 Pages
  • Computers + Internet, Machine Theory
  • Series Name: Adaptive Computation and Machine Learning

Description



About the Book



A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.



Book Synopsis



A comprehensive introduction to machine learning that uses probabilistic models and inference as a unifying approach.

Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach.

The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package--PMTK (probabilistic modeling toolkit)--that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.



Review Quotes




This comprehensive book should be of great interest to learners and practitioners in the field of machine learning.--British Computer Society--



About the Author



Kevin P. Murphy is a Senior Staff Research Scientist at Google Research.
Dimensions (Overall): 9.1 Inches (H) x 8.2 Inches (W) x 1.7 Inches (D)
Weight: 4.3 Pounds
Suggested Age: 22 Years and Up
Number of Pages: 1104
Genre: Computers + Internet
Sub-Genre: Machine Theory
Series Title: Adaptive Computation and Machine Learning
Publisher: MIT Press
Format: Hardcover
Author: Kevin P Murphy
Featured book lists: Textbooks
Language: English
Street Date: August 24, 2012
TCIN: 1003665393
UPC: 9780262018029
Item Number (DPCI): 315-00-0236
Origin: Made in the USA or Imported
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Estimated ship dimensions: 1.7 inches length x 8.2 inches width x 9.1 inches height
Estimated ship weight: 4.3 pounds
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