A first course in machine learning / Simon Rogers, Mark Girolami.

By:

Rogers, Simon, 1979-

Contributor(s):

Girolami, Mark, 1963-

Material type: Text

TextSeries: Machine learning & pattern recognition seriesPublication details: Boca Raton : CRC Press, 2011.Description: xx, 285 p. ; 23 cmISBN:

9781439824146

Subject(s):

Machine learning

DDC classification:

006.31 23

Contents:

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.

Summary: A First Course in Machine Learning covers the core mathematical and statistical techniques needed to understand some of the most popular machine learning algorithms. The algorithms presented span the main problem areas within machine learning: classification, clustering and projection. The text gives detailed descriptions and derivations for a small number of algorithms rather than cover many algorithms in less detail.

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Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Books	Main library General Stacks	006.31 / RO.F 2011 (Browse shelf(Opens below))	1	Available		011649

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Includes bibliographical references and index.

A First Course in Machine Learning covers the core mathematical and statistical techniques needed to understand some of the most popular machine learning algorithms. The algorithms presented span the main problem areas within machine learning: classification, clustering and projection. The text gives detailed descriptions and derivations for a small number of algorithms rather than cover many algorithms in less detail.

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