Pattern Recognition and Machine Learning
3111 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.
-
Medical Informatics
-
An Introduction to Homological Algebra
Rotman, Joseph J.
-
The Taste of Bread
Calvel, Raymond; Wirtz, Ronald L.
-
Regression Methods in Biostatistics
Vittinghoff, Eric; Glidden, David V.; Shiboski, Stephen C.; McCulloch, Charles E.
-
A Course in Mathematical Statistics a...
Bhattacharya, Rabi; Waymire, Edward C.
-
Mathematics and Its History
Stillwell, John
-
Statistics and Analysis of Scientifi...
Bonamente, Massimiliano
-
Complex Analysis
Lang, Serge
-
Advanced Topics in the Arithmetic of...
Silverman, Joseph H.
-
Classical Descriptive Set Theory
Kechris, Alexander
-
Exploring Science Through Science Fi...
Luokkala, Barry B.
-
Handbook of Neurochemistry and Molec...
-
Mitochondria and the Heart
-
Handbook of Marriage and the Family
-
Geometry
Borovik, Alexandre V.; White, Neil; Gelfand, Israel M.