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Check Availability Lawrence Library / Main Collection: Q325.5 .R64 2012Library Info

Author LinkRogers, Simon,1979-
Title LinkA first course in machine learning / Simon Rogers, Mark Girolami.
Imprint Boca Raton : CRC Press, 2012 .
Description xx, 285 p. :  ill. ;  25 cm.
Type of Material Book
Series ( Chapman & Hall/CRC machine learning & pattern recognition series )
Series ( Chapman & Hall/CRC machine learning & pattern recognition series.)
Bibliography Note Includes bibliographical references and index.
Summary "Machine Learning is rapidly becoming one of the most important areas of general practice, research and development activity within Computing Science. This is reflected in the scale of the academic research area devoted to the subject and the active recruitment of Machine Learning specialists by major international banks and financial institutions as well as companies such as Microsoft, Google, Yahoo and Amazon. This growth can be partly explained by the increase in the quantity and diversity of measurements we are able to make of the world. A particularly fascinating example arises from the wave of new biological measurement technologies that have preceded the sequencing of the first genomes. It is now possible to measure the detailed molecular state of an organism in manners that would have been hard to imagine only a short time ago. Such measurements go far beyond our understanding of these organisms and Machine Learning techniques have been heavily involved in the distillation of useful structure from them. This book is based on material taught in a Machine Learning course in the School of Computing Science at the University of Glasgow, UK. The course, presented to final year undergraduates and taught by postgraduates, is made up of 20 hour-long lectures and 10 hour-long laboratory sessions. In such a short teaching period, it is impossible to cover more than a small fraction of the material that now comes under the banner of Machine Learning. Our intention when teaching this course therefore, is to present the core mathematical and statistical techniques required to understand some of the most popular Machine Learning algorithms and then present a few of these algorithms that span the main problem areas within Machine Learning: classification, clus- tering"-- Provided by publisher.
Subject LinkMachine learning.
Add.Author LinkGirolami, Mark, 1963-

System Number 000678671
ISBN Link9781439824146 (hardback)
Link1439824142 (hardback)

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