First Course in Machine Learning (Record no. 1433121)

MARC details
000 -LEADER
fixed length control field 01719nam a22002777a 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250630144223.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 250630b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781032937908
040 ## - CATALOGING SOURCE
Original cataloging agency CSL
Transcribing agency CSL
041 ## - LANGUAGE CODE
Source of code eng
Language code of text/sound track or separate title eng
084 ## - COLON CLASSIFICATION NUMBER
Classification number D65,8(B):(S:72) Q2;Q7
Assigning agency CSL
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Rogers, Simon
Relator term author.
9 (RLIN) 814926
245 ## - TITLE STATEMENT
Title First Course in Machine Learning
250 ## - EDITION STATEMENT
Edition statement 2nd ed.
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Boca Raton :
Name of publisher, distributor, etc. CRC Press/Taylor & Franics,
Date of publication, distribution, etc. 2017.
300 ## - PHYSICAL DESCRIPTION
Extent xxix, 397p.
Other physical details : ill.
Dimensions ; 23 cm.
490 ## - SERIES STATEMENT
Series statement Chapman & Hall/CRC Machine Learning & Pattern Recognition series
500 ## - GENERAL NOTE
General note Includes index.
520 ## - SUMMARY, ETC.
Summary, etc. A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings, and goes all the way to the frontiers of the subject such as infinite mixture models, GPs, and MCMC." —Devdatt Dubhashi, Professor, Department of Computer Science and Engineering, Chalmers University, Sweden "This textbook manages to be easier to read than other comparable books in the subject while retaining all the rigorous treatment needed. The new chapters put it at the forefront of the field by covering topics that have become mainstream in machine learning over the last decade.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Bayesian methods.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element classification.
9 (RLIN) 229842
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Linear modelling.
9 (RLIN) 814927
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Clustering.
9 (RLIN) 733203
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Girolami, Mark
Relator term author.
9 (RLIN) 472463
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Colon Classification (CC)
Koha item type Textual
Edition 2nd ed.
Classification part D65,8(B):(S:72) Q2;Q7
Suppress in OPAC No
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Source of acquisition Total Checkouts Full call number Barcode Date last seen Date last checked out Price effective from Koha item type
    Colon Classification (CC)     Central Science Library Central Science Library 2024-10-23 Classic Book Service 1 D65,8(B):(S:72) Q2;Q7 SL1655959 2026-01-13 2025-11-29 2025-06-30 Textual
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