(0)
 
Pattern Recognition and Machine Learning
by Christopher M. Bishop

Overview - 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.  Read more...

 
Hardcover
  • $94.95

Add to Cart + Add to Wishlist

In Stock. Usually ships within 24 hours.

Free Shipping is not available for this item.

Not a member? Join Today!
 
 
New & Used Marketplace 41 copies from $29.20
 
 
 

More About Pattern Recognition and Machine Learning by Christopher M. Bishop
 
 
 
Overview
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.

 
Details
  • ISBN-13: 9780387310732
  • ISBN-10: 0387310738
  • Publisher: Springer
  • Publish Date: August 2006
  • Page Count: 738

Series: Information Science and Statistics

Related Categories

Books > Computers & Internet > Intelligence (AI) & Semantics
Books > Computers & Internet > Computer Vision & Pattern Recognition

 
BAM Customer Reviews

DISCUSSION