You don't need to own a Kindle device to enjoy Kindle books. Download one of our FREE Kindle apps to start reading Kindle books on all your devices.

  • Apple
    Apple
  • Android
    Android
  • Windows Phone
    Windows Phone
  • Click here to download from Amazon appstore
    Android

To get the free app, enter your mobile phone number.

kcpAppSendButton

Buying Options

This title is not currently available for purchase
<Embed>
Pattern Recognition and Machine Learning (Information Science and Statistics) by [Bishop, Christopher M. ]
Kindle App Ad

Follow the Author

Something went wrong. Please try your request again later.


Pattern Recognition and Machine Learning (Information Science and Statistics) Kindle Edition

4.0 out of 5 stars 172 customer reviews

See all 4 formats and editions Hide other formats and editions
Amazon Price
New from Used from
Kindle
$11.72

Length: 738 pages Enhanced Typesetting: Enabled Page Flip: Enabled
Language: English
  • Due to its large file size, this book may take longer to download

Item Under Review

This book is currently unavailable because there are significant quality issues with the source file supplied by the publisher.

The publisher has been notified and we will make the book available as soon as we receive a corrected file. As always, we value customer feedback.


Winter Sale
Up to 70% off on over 300 Kindle Books. Sale ends on 31st August 2019 at 11:59 pm AEST. Shop now

Product description

Review

From the reviews:

"This beautifully produced book is intended for advanced undergraduates, PhD students, and researchers and practitioners, primarily in the machine learning or allied areas...A strong feature is the use of geometric illustration and intuition...This is an impressive and interesting book that might form the basis of several advanced statistics courses. It would be a good choice for a reading group." John Maindonald for the Journal of Statistical Software

"In this book, aimed at senior undergraduates or beginning graduate students, Bishop provides an authoritative presentation of many of the statistical techniques that have come to be considered part of ‘pattern recognition’ or ‘machine learning’. … This book will serve as an excellent reference. … With its coherent viewpoint, accurate and extensive coverage, and generally good explanations, Bishop’s book is a useful introduction … and a valuable reference for the principle techniques used in these fields." (Radford M. Neal, Technometrics, Vol. 49 (3), August, 2007)

"This book appears in the Information Science and Statistics Series commissioned by the publishers. … The book appears to have been designed for course teaching, but obviously contains material that readers interested in self-study can use. It is certainly structured for easy use. … For course teachers there is ample backing which includes some 400 exercises. … it does contain important material which can be easily followed without the reader being confined to a pre-determined course of study." (W. R. Howard, Kybernetes, Vol. 36 (2), 2007)

"Bishop (Microsoft Research, UK) has prepared a marvelous book that provides a comprehensive, 700-page introduction to the fields of pattern recognition and machine learning. Aimed at advanced undergraduates and first-year graduate students, as well as researchers and practitioners, the book assumes knowledge of multivariate calculus and linear algebra … . Summing Up: Highly recommended. Upper-division undergraduates through professionals." (C. Tappert, CHOICE, Vol. 44 (9), May, 2007)

"The book is structured into 14 main parts and 5 appendices. … The book is aimed at PhD students, researchers and practitioners. It is well-suited for courses on machine learning, statistics, computer science, signal processing, computer vision, data mining, and bio-informatics. Extensive support is provided for course instructors, including more than 400 exercises, lecture slides and a great deal of additional material available at the book’s web site … ." (Ingmar Randvee, Zentralblatt MATH, Vol. 1107 (9), 2007)

"This new textbook by C. M. Bishop is a brilliant extension of his former book ‘Neural Networks for Pattern Recognition’. It is written for graduate students or scientists doing interdisciplinary work in related fields. … In summary, this textbook is an excellent introduction to classical pattern recognition and machine learning (in the sense of parameter estimation). A large number of very instructive illustrations adds to this value." (H. G. Feichtinger, Monatshefte für Mathematik, Vol. 151 (3), 2007)

"Author aims this text at advanced undergraduates, beginning graduate students, and researchers new to machine learning and pattern recognition. … Pattern Recognition and Machine Learning provides excellent intuitive descriptions and appropriate-level technical details on modern pattern recognition and machine learning. It can be used to teach a course or for self-study, as well as for a reference. … I strongly recommend it for the intended audience and note that Neal (2007) also has given this text a strong review to complement its strong sales record." (Thomas Burr, Journal of the American Statistical Association, Vol. 103 (482), June, 2008)

"This accessible monograph seeks to provide a comprehensive introduction to the fields of pattern recognition and machine learning. It presents a unified treatment of well-known statistical pattern recognition techniques. … The book can be used by advanced undergraduates and graduate students … . The illustrative examples and exercises proposed at the end of each chapter are welcome … . The book, which provides several new views, developments and results, is appropriate for both researchers and students who work in machine learning … ." (L. State, ACM Computing Reviews, October, 2008)

"Chris Bishop’s … technical exposition that is at once lucid and mathematically rigorous. … In more than 700 pages of clear, copiously illustrated text, he develops a common statistical framework that encompasses … machine learning. … it is a textbook, with a wide range of exercises, instructions to tutors on where to go for full solutions, and the color illustrations that have become obligatory in undergraduate texts. … its clarity and comprehensiveness will make it a favorite desktop companion for practicing data analysts." (H. Van Dyke Parunak, ACM Computing Reviews, Vol. 49 (3), March, 2008)

Product Description

This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Product details

  • Format: Kindle Edition
  • File Size: 32592 KB
  • Print Length: 738 pages
  • Sold by: Amazon Australia Services, Inc.
  • Language: English
  • ASIN: B07CMM4TWS
  • Text-to-Speech: Enabled
  • X-Ray:
  • Word Wise: Not Enabled
  • Screen Reader: Supported
  • Enhanced Typesetting: Enabled
  • Average Customer Review: Be the first to review this item
click to open popover

No customer reviews


Review this product

Share your thoughts with other customers

Most helpful customer reviews on Amazon.com

Amazon.com: 4.0 out of 5 stars 172 reviews
e
5.0 out of 5 starsStill (one of) the best
18 January 2016 - Published on Amazon.com
Verified Purchase
64 people found this helpful
Joe
1.0 out of 5 starsKindle Version is Unusable
13 May 2018 - Published on Amazon.com
Verified Purchase
17 people found this helpful
Claudio A. Rodrigues
2.0 out of 5 starsSo many formatting issues in the Kindle version!
12 May 2018 - Published on Amazon.com
Verified Purchase
9 people found this helpful
IB
3.0 out of 5 starsOverall good, lots of potential for improvement
19 May 2015 - Published on Amazon.com
Verified Purchase
26 people found this helpful
J. MEJIA Muñoz
1.0 out of 5 starsIn general, most of the topics are not clearly ...
23 April 2018 - Published on Amazon.com
Verified Purchase
8 people found this helpful