"Pattern Recognition and Machine Learning: Solutions Exercises" by Christopher M. Bishop
"Pattern Recognition and Machine Learning: Solutions Exercises" by Christopher M. Bishop
Information Science and Statistics
Sрringеr Science+Business Media | 2006 | ISBN: 0387310732 0387310738 | 101 pages | PDF | 1 MB
Information Science and Statistics
Sрringеr Science+Business Media | 2006 | ISBN: 0387310732 0387310738 | 101 pages | PDF | 1 MB
Example solutions for a subset of the exercises are available from the book. This issue is supported by a great deal of additional material, and the reader is encouraged to visit the book web site for the latest information. A volume deals with practical aspects of pattern recognition and machine learning, and will include free software implementations of the key algorithms along with example data sets.
Contents
Chapter 1: Introduction
Chapter 2: Probability Distributions
Chapter 3: Linear Models for Regression
Chapter 4: Linear Models for Classification
Chapter 5: Neural Networks
Chapter 6: Kernel Methods
Chapter 7: Sparse Kernel Machines
Chapter 8: Graphical Models
Chapter 9: Mixture Models and EM
Chapter 10: Approximate Inference
Chapter 11: Sampling Methods
Chapter 12: Continuous Latent Variables
Chapter 13: Sequential Data
Chapter 14: Combining Models
with TOC BookMarkLinks
"Pattern Recognition and Machine Learning: Solutions Exercises" by Christopher M. Bishop
