Rogers, Simon, author.
A first course in machine learning / Simon Rogers; Mark Girolami. - Second edition - Boca Raton : CRC Press, c2017. - xxix, 397 pages : illustrations (black and white) ; 24 cm. - Chapman & Hall/CRC machine learning & pattern recognition series .
Includes e-book access.
Previous edition: 2012.
"A Chapman & Hall book."
Includes bibliographical references and index.
Linear Modelling: A Least Squares Approach. Linear Modelling: A Maximum Likelihood Approach. The Bayesian Approach to Machine Learning. Bayesian Inference. Classification. Clustering. Principal Components Analysis and Latent Variable Models. Further Topics in Markov Chain Monte Carlo. Classification and Regression with Gaussian Processes. Dirichlet Process models.
The new edition of this popular, undergraduate textbook has been revised and updated to reflect current growth areas in Machine Learning. The new edition includes three new chapters with more detailed discussion of Markov Chain Monte Carlo techniques, Classification and Regression with Gaussian Processes, and Dirichlet Process models.
In English text.
978-14-8738484 (Hardback)
Machine learning.
Computers and IT.
CIR Q 325.5 / R64 2017
A first course in machine learning / Simon Rogers; Mark Girolami. - Second edition - Boca Raton : CRC Press, c2017. - xxix, 397 pages : illustrations (black and white) ; 24 cm. - Chapman & Hall/CRC machine learning & pattern recognition series .
Includes e-book access.
Previous edition: 2012.
"A Chapman & Hall book."
Includes bibliographical references and index.
Linear Modelling: A Least Squares Approach. Linear Modelling: A Maximum Likelihood Approach. The Bayesian Approach to Machine Learning. Bayesian Inference. Classification. Clustering. Principal Components Analysis and Latent Variable Models. Further Topics in Markov Chain Monte Carlo. Classification and Regression with Gaussian Processes. Dirichlet Process models.
The new edition of this popular, undergraduate textbook has been revised and updated to reflect current growth areas in Machine Learning. The new edition includes three new chapters with more detailed discussion of Markov Chain Monte Carlo techniques, Classification and Regression with Gaussian Processes, and Dirichlet Process models.
In English text.
978-14-8738484 (Hardback)
Machine learning.
Computers and IT.
CIR Q 325.5 / R64 2017