Mathematics for machine learning / (Record no. 43464)

MARC details
000 -LEADER
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003 - CONTROL NUMBER IDENTIFIER
control field CUTN
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240906123920.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 191130s2020 enk b 001 0 eng
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781108470049
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781108455145
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
Cancelled/invalid ISBN 9781108679930
041 ## - LANGUAGE CODE
Language English
042 ## - AUTHENTICATION CODE
Authentication code pcc
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.31
Edition number 23
Item number DEI
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Deisenroth, Marc Peter,
245 10 - TITLE STATEMENT
Title Mathematics for machine learning /
Statement of responsibility, etc Marc Peter Deisenroth, A. Aldo Faisal, Cheng Soon Ong.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Cambridge, United Kingdom :
Name of publisher, distributor, etc Cambridge University Press,
Date of publication, distribution, etc 2020.
300 ## - PHYSICAL DESCRIPTION
Extent xvii, 371 pages :
Other physical details illustrations (some color) ;
Dimensions 26 cm.
505 0# - FORMATTED CONTENTS NOTE
Contents Introduction and motivation -- Linear algebra -- Analytic geometry -- Matrix decompositions -- Vector calculus -- Probability and distribution -- Continuous optimization -- When models meet data -- Linear regression -- Dimensionality reduction with principal component analysis -- Density estimation with Gaussian mixture models -- Classification with support vector machines.
520 ## - SUMMARY, ETC.
Summary, etc "The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability, and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models, and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts"--
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Faisal, A. Aldo,
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Ong, Cheng Soon,
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type General Books
100 1# - MAIN ENTRY--PERSONAL NAME
Relator term author.
263 ## - PROJECTED PUBLICATION DATE
Projected publication date 1912
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
General subdivision Mathematics.
700 1# - ADDED ENTRY--PERSONAL NAME
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Relator term author.
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Online version:
Main entry heading Deisenroth, Marc Peter.
Title Mathematics for machine learning.
Place, publisher, and date of publication Cambridge, United Kingdom ; New York : Cambridge University Press, 2020.
International Standard Book Number 9781108679930
Record control number (DLC) 2019040763
906 ## - LOCAL DATA ELEMENT F, LDF (RLIN)
a 7
b cbc
c orignew
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g y-gencatlg
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Home library Location Shelving location Date of Cataloging Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
    Dewey Decimal Classification     Non-fiction CUTN Central Library CUTN Central Library Generalia 06/09/2024   006.31 DEI 49459 06/09/2024 06/09/2024 General Books

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