A First Course in Machine Learning

Rogers, S. and Girolami, M. (2011) A First Course in Machine Learning. Chapman & Hall / CRC. ISBN 9781439824146

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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.

Requiring minimal mathematical prerequisites, the classroom-tested material in this text offers a concise, accessible introduction to machine learning. It provides students with the knowledge and confidence to explore the machine learning literature and research specific methods in more detail.

Item Type:Books
Glasgow Author(s) Enlighten ID:Rogers, Dr Simon
Authors: Rogers, S., and Girolami, M.
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
College/School:College of Science and Engineering > School of Computing Science
Research Group:Inference Dynamics and Interaction
Publisher:Chapman & Hall / CRC
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