Machine Learning: A Probabilistic Perspective (Adaptive Computation and Machine Learning series) Illustrated Edition

4.4 out of 5 stars 296 ratings
ISBN-13: 978-0262018029
ISBN-10: 0262018020
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Due Date: Aug 10, 2022 Rental Details
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Editorial Reviews

Review

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

Review

This book will be an essential reference for practitioners of modern machine learning. It covers the basic concepts needed to understand the field as whole, and the powerful modern methods that build on those concepts. In Machine Learning, the language of probability and statistics reveals important connections between seemingly disparate algorithms and strategies.Thus, its readers will become articulate in a holistic view of the state-of-the-art and poised to build the next generation of machine learning algorithms.

David Blei, Princeton University

Product details

  • Publisher ‏ : ‎ The MIT Press; Illustrated edition (August 24, 2012)
  • Language ‏ : ‎ English
  • Hardcover ‏ : ‎ 1104 pages
  • ISBN-10 ‏ : ‎ 0262018020
  • ISBN-13 ‏ : ‎ 978-0262018029
  • Reading age ‏ : ‎ 18 years and up
  • Item Weight ‏ : ‎ 4.2 pounds
  • Dimensions ‏ : ‎ 8.25 x 1.79 x 9.27 inches
  • Customer Reviews:
    4.4 out of 5 stars 296 ratings

About the author

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Kevin Patrick Murphy was born in Ireland, grew up in England (BA from Cambridge),

and went to graduate school in the USA (MEng from U. Penn, PhD from UC Berkeley,

Postdoc at MIT). In 2004, he became a professor of computer science and statistics

at the University of British Columbia in Vancouver, Canada. In 2011, he went to

Google in Mountain View, California for his sabbatical. In 2012, he

converted to a full-time research scientist position at Google. Kevin has

published over 50 papers in refereed conferences and journals related

to machine learning and graphical models. He has recently published

an 1100-page textbook called "Machine Learning: a Probabilistic

Perspective" (MIT Press, 2012).

Customer reviews

4.4 out of 5 stars
4.4 out of 5
296 global ratings

Top reviews from the United States

Reviewed in the United States on December 8, 2015
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Reviewed in the United States on April 27, 2019
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Reviewed in the United States on June 9, 2020
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Reviewed in the United States on July 11, 2017
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Reviewed in the United States on June 7, 2017
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Reviewed in the United States on June 5, 2021

Top reviews from other countries

Kai_S
5.0 out of 5 stars awesome book
Reviewed in the United Kingdom on November 24, 2017
16 people found this helpful
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newway
5.0 out of 5 stars sometimes you need to go back to the details
Reviewed in the United Kingdom on April 6, 2019
2 people found this helpful
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Alvaro
4.0 out of 5 stars My favourite machine learning book
Reviewed in the United Kingdom on August 11, 2018
JC
5.0 out of 5 stars The reference book on modern Machine Learning
Reviewed in the United Kingdom on April 19, 2019
phong vo
5.0 out of 5 stars Better than PRML of Bishop in my opinion
Reviewed in the United Kingdom on June 4, 2017
2 people found this helpful
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