Pattern Recognition and Machine Learning
8
%
2194 Kč 2 379 Kč
Sleva až 70% u třetiny knih
This is the first textbook on pattern recognition to present the Bayesian viewpoint. It presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible, and it uses graphical models to describe probability distributions.
Autor: | Bishop, Christopher M. |
Nakladatel: | Springer-Verlag New York Inc. |
ISBN: | 9780387310732 |
Rok vydání: | 2006 |
Jazyk : | Angličtina |
Vazba: | Hardback |
Počet stran: | 738 |
Mohlo by se vám také líbit..
-
Neural Networks for Pattern Recognition
Bishop, Christopher M.
-
Introduction to Biometrics
Maltoni, Davide; Maio, Dario; Jain, Anil; Prabhakar, Salil
-
Grids and Service-Oriented Architect...
-
Closing the Gap Between ASIC & Custom
Chinnery, David; Keutzer, Kurt
-
Advances in Pervasive Computing and ...
-
Data Mining for Social Network Data
-
Medical Informatics
-
An Introduction to Homological Algebra
Rotman, Joseph J.
-
Art and Archaeology
-
A First Course in Bayesian Statistica...
Peter Hoffmann
-
Exploring Science Through Science Fi...
Luokkala, Barry B.
-
The Observer's Sky Atlas
Erich Karkoschka
-
Pediatric Dialysis
-
Handbook of Neurochemistry and Molec...
-
Handbook of Neurochemistry and Molec...
-
To Queue or Not to Queue
Hassin, Refael (Tel Aviv University, Israel)