Coverart for item
The Resource Machine learning : a probabilistic perspective, Kevin P. Murphy

Machine learning : a probabilistic perspective, Kevin P. Murphy

Label
Machine learning : a probabilistic perspective
Title
Machine learning
Title remainder
a probabilistic perspective
Statement of responsibility
Kevin P. Murphy
Creator
Author
Subject
Genre
Language
eng
Summary
"This textbook offers a comprehensive and self-contained introduction to the field of machine learning, based on a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package--PMTK (probabilistic modeling toolkit)--that is freely available online"--Back cover
Member of
Cataloging source
YDXCP
Dewey number
006.3/1
Illustrations
illustrations
Index
index present
LC call number
Q325.5
LC item number
.M87 2012
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Series statement
Adaptive computation and machine learning series
Label
Machine learning : a probabilistic perspective, Kevin P. Murphy
Link
http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=480968
Instantiates
Publication
Bibliography note
Includes bibliographical references and indexes
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • ""Contents""; ""Preface""; ""1 Introduction""; ""2 Probability""; ""3 Generative Models for Discrete Data""; ""4 Gaussian Models""; ""5 Bayesian Statistics""; ""6 Frequentist Statistics""; ""7 Linear Regression""; ""8 Logistic Regression""; ""9 Generalized Linear Models and the Exponential Family""; ""10 Directed Graphical Models (Bayes Nets)""; ""11 Mixture Models and the EM Algorithm""; ""12 Latent Linear Models""; ""13 Sparse Linear Models""; ""14 Kernels""; ""15 Gaussian Processes""; ""16 Adaptive Basis Function Models""; ""17 Markov and Hidden Markov Models""; ""18 State Space Models""
  • ""19 Undirected Graphical Models (Markov Random Fields)""""20 Exact Inference for Graphical Models""; ""21 Variational Inference""; ""22 More Variational Inference""; ""23 Monte Carlo Inference""; ""24 Markov Chain Monte Carlo (MCMC) Inference""; ""25 Clustering""; ""26 Graphical Model Structure Learning""; ""27 Latent Variable Models for Discrete Data""; ""28 Deep Learning""; ""Notation""; ""Bibliography""; ""Index to Code""; ""Index to Keywords""
Control code
ocn810414751
Dimensions
unknown
Extent
1 online resource (xxix, 1067 pages)
Form of item
online
Isbn
9780262305242
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other physical details
illustrations (chiefly color).
Specific material designation
remote
Stock number
134420A7-297E-48A3-B022-D185EDC1FCE9
System control number
(OCoLC)810414751
Label
Machine learning : a probabilistic perspective, Kevin P. Murphy
Link
http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&AN=480968
Publication
Bibliography note
Includes bibliographical references and indexes
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • ""Contents""; ""Preface""; ""1 Introduction""; ""2 Probability""; ""3 Generative Models for Discrete Data""; ""4 Gaussian Models""; ""5 Bayesian Statistics""; ""6 Frequentist Statistics""; ""7 Linear Regression""; ""8 Logistic Regression""; ""9 Generalized Linear Models and the Exponential Family""; ""10 Directed Graphical Models (Bayes Nets)""; ""11 Mixture Models and the EM Algorithm""; ""12 Latent Linear Models""; ""13 Sparse Linear Models""; ""14 Kernels""; ""15 Gaussian Processes""; ""16 Adaptive Basis Function Models""; ""17 Markov and Hidden Markov Models""; ""18 State Space Models""
  • ""19 Undirected Graphical Models (Markov Random Fields)""""20 Exact Inference for Graphical Models""; ""21 Variational Inference""; ""22 More Variational Inference""; ""23 Monte Carlo Inference""; ""24 Markov Chain Monte Carlo (MCMC) Inference""; ""25 Clustering""; ""26 Graphical Model Structure Learning""; ""27 Latent Variable Models for Discrete Data""; ""28 Deep Learning""; ""Notation""; ""Bibliography""; ""Index to Code""; ""Index to Keywords""
Control code
ocn810414751
Dimensions
unknown
Extent
1 online resource (xxix, 1067 pages)
Form of item
online
Isbn
9780262305242
Media category
computer
Media MARC source
rdamedia
Media type code
c
Other physical details
illustrations (chiefly color).
Specific material designation
remote
Stock number
134420A7-297E-48A3-B022-D185EDC1FCE9
System control number
(OCoLC)810414751

Library Locations

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      Collins Hall 2nd Floor Waubonsee Community College Route 47 at Waubonsee Drive, Sugar Grove, IL, 60554-9454, US
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