Pattern Recognition and Machine Learning (Information Science and Statistics)

$94.95 $68.03

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

Quantity

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.

Author

Christopher M. Bishop

Binding

Hardcover

EAN

9780387310732

EANList

9780387310732

ISBN

0387310738

IsEligibleForTradeIn

1

ItemDimensions

180, hundredths-inches, 930, hundredths-inches, 390, hundredths-pounds, 730, hundredths-inches

Label

Springer

Languages

English, Unknown, English, Original Language, English, Published

Manufacturer

Springer

NumberOfItems

1

NumberOfPages

738

PackageQuantity

1

ProductGroup

Book

PublicationDate

2007-10-01

Publisher

Springer

Studio

Springer

TradeInValue

3419, USD, $34.19