A first course in machine learning / (Record no. 6915)
[ view plain ]
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
---|---|
fixed length control field | 120222s2011 flu b 001 0 eng |
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER | |
LC control number | 2011039389 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
International Standard Book Number | 9781439824146 |
035 ## - SYSTEM CONTROL NUMBER | |
System control number | (Sirsi) u8012 |
040 ## - CATALOGING SOURCE | |
Original cataloging agency | EG-CaNU |
Transcribing agency | EG-CaNU |
Modifying agency | EG-CaNU |
042 ## - AUTHENTICATION CODE | |
Authentication code | ncode |
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
Classification number | 006.31 |
Edition number | 23 |
100 1# - MAIN ENTRY--PERSONAL NAME | |
Personal name | Rogers, Simon, |
Dates associated with a name | 1979- |
9 (RLIN) | 14491 |
245 12 - TITLE STATEMENT | |
Title | A first course in machine learning / |
Statement of responsibility, etc. | Simon Rogers, Mark Girolami. |
260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
Place of publication, distribution, etc. | Boca Raton : |
Name of publisher, distributor, etc. | CRC Press, |
Date of publication, distribution, etc. | 2011. |
300 ## - PHYSICAL DESCRIPTION | |
Extent | xx, 285 p. ; |
Dimensions | 23 cm. |
490 0# - SERIES STATEMENT | |
Series statement | Machine learning & pattern recognition series |
504 ## - BIBLIOGRAPHY, ETC. NOTE | |
Bibliography, etc. note | Includes bibliographical references and index. |
505 0# - FORMATTED CONTENTS NOTE | |
Formatted contents note | 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. |
520 ## - SUMMARY, ETC. | |
Summary, etc. | 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. |
596 ## - | |
-- | 1 |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
Topical term or geographic name entry element | Machine learning. |
9 (RLIN) | 14492 |
700 1# - ADDED ENTRY--PERSONAL NAME | |
Personal name | Girolami, Mark, |
Dates associated with a name | 1963- |
9 (RLIN) | 14493 |
Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Total Checkouts | Total Renewals | Full call number | Barcode | Date last seen | Date last checked out | Copy number | Price effective from | Koha item type |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Dewey Decimal Classification | Main library | Main library | General Stacks | 01/26/2020 | AHRA-P | 3 | 1 | 006.31 / RO.F 2011 | 011649 | 05/29/2023 | 04/26/2023 | 1 | 11/24/2019 | Books |