Pattern Recognition and Machine Learning (Information Science and Statistics)

Pattern Recognition and Machine Learning (Information Science and Statistics) by Christopher M. Bishop

Quick Overview

Written By: Christopher M. Bishop
Publisher: Springer

Binding: Hardcover
Edition: 1st ed. 2006. Corr. 2nd printing 2011
Language: English
EAN: 9780387310732
Feature: Springer
ISBN: 0387310738
Number Of Items: 1
Number Of Pages: 738
Publication Date: 2010-02-15
Manufacturer: Springer

Availability: Usually dispatched within 1-2 business days

Price Details
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Product Features


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.

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