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A first course in machine learning / (Record no. 32123)

000 -LEADER
fixed length control field 02644cam a2200241 a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20200123111014.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 111020s2012 flua b 001 0 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781439824146 (hardback)
041 07 - Language
Language code of text/sound track or separate title eng
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Edition number 23
Item number R724
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Rogers, Simon,
Dates associated with a name 1979-
9 (RLIN) 35453
245 12 - IMMEDIATE SOURCE OF ACQUISITION NOTE
Title A first course in machine learning /
Statement of responsibility, etc Simon Rogers, Mark Girolami.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Boca Raton, FL :
Name of publisher, distributor, etc CRC Press,
Date of publication, distribution, etc 2012.
300 ## - PHYSICAL DESCRIPTION
Extent xx, 285 p. :
Other physical details ill. ;
Dimensions 25 cm.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
520 ## - SUMMARY, ETC.
Summary, etc "Machine Learning is rapidly becoming one of the most important areas of general practice, research and development activity within Computing Sci- ence. This is re ected 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 nancial 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 on a Machine Learning course in the School of Computing Science at the University of Glasgow, UK. The course, presented to nal year undergraduates and taught 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 inten- tion 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: classi cation, clus- tering"--
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning.
9 (RLIN) 2665
Topical term or geographic name as entry element BUSINESS & ECONOMICS / Statistics.
Source of heading or term bisacsh
9 (RLIN) 35454
Topical term or geographic name as entry element COMPUTERS / General.
Source of heading or term bisacsh
9 (RLIN) 35455
Topical term or geographic name as entry element COMPUTERS / Database Management / Data Mining.
Source of heading or term bisacsh
9 (RLIN) 35022
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Girolami, Mark,
Dates associated with a name 1963-
9 (RLIN) 35456
Relator term author
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme
Item type Book
Copies
Price effective from Permanent location Date last seen Not for loan Date acquired Date last borrowed Source of classification or shelving scheme Total Checkouts Koha item type Barcode Damaged status Lost status Withdrawn status Current location Full call number
2015-06-09AUM Main Library2023-05-08 2015-06-092023-02-02 5BookAUM-021333   AUM Main Library006.31 R724

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