Pattern Recognition and Machine Learning
4188 Kč
Expedujeme 1 až 2 dny
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.
-
Closing the Gap Between ASIC & Custom
Chinnery, David; Keutzer, Kurt
-
Data Mining for Social Network Data
-
Introduction to Biometrics
Maltoni, Davide; Maio, Dario; Jain, Anil; Prabhakar, Salil
-
Grids and Service-Oriented Architect...
-
Medical Informatics
-
Generalized Linear Models With Examp...
Dunne Peter
-
Exploring Science Through Science Fi...
Luokkala, Barry B.
-
The Observer's Sky Atlas
Erich Karkoschka
-
Printed Organic and Molecular Electr...
-
Modern Food Microbiology
Jay, James M.; Loessner, Martin J.; Golden, David A.
-
Fundamentals of Radiation Materials ...
Was, Gary S.
-
Differential Forms in Algebraic Topo...
Bott, Raoul; Tu, Loring W.
-
Instructional Design: The ADDIE Appr...
Branch, Robert Maribe
-
Mathematical Biology
Murray, James T.
-
Naive Lie Theory
Stillwell, John