Mathematics for machine learning / (Record no. 6048)

MARC details
000 -LEADER
fixed length control field 02672cam a22003618i 4500
001 - CONTROL NUMBER
control field 21336577
003 - CONTROL NUMBER IDENTIFIER
control field BD-ChPU
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20221129112128.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 191130s2020 enk b 001 0 eng
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER
LC control number 2019040762
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781108470049
Qualifying information (hardback)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781108455145
Qualifying information (paperback)
040 ## - CATALOGING SOURCE
Original cataloging agency LBSOR/DLC
Language of cataloging eng
Description conventions rda
Transcribing agency DLC
Modifying agency BD-ChPU
042 ## - AUTHENTICATION CODE
Authentication code pcc
050 00 - LIBRARY OF CONGRESS CALL NUMBER
Classification number Q325.5
Item number .D45 2020
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 006.3/1 D325m 2019
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Deisenroth, Marc Peter,
Relator term author.
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 :
Name of publisher, distributor, etc Cambridge University Press,
Date of publication, distribution, etc 2019.
263 ## - PROJECTED PUBLICATION DATE
Projected publication date 1912
300 ## - PHYSICAL DESCRIPTION
Extent iii,411 pages :
Other physical details illustrations ;
Dimensions 27 cm.
504 ## - BIBLIOGRAPHY, ETC. NOTE
Bibliography, etc Includes bibliographical references and index.
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note 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"--
526 ## - STUDY PROGRAM INFORMATION NOTE
Program name Mathematics
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine learning
General subdivision Mathematics.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Faisal, A. Aldo,
Relator term author.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Ong, Cheng Soon,
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
d 1
e ecip
f 20
g y-gencatlg
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Koha item type Books
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 Full call number Barcode Date last seen Copy number Price effective from Koha item type
    Dewey Decimal Classification     Premier University Department of Mathematics Library Premier University Department of Mathematics Library 23/10/2022 purchase 006.3/1 D325m 2019 26075 08/11/2022 1 08/11/2022 Books
    Dewey Decimal Classification     Premier University Department of Mathematics Library Premier University Department of Mathematics Library 23/10/2022 purchase 006.3/1 D325m 2019 26076 08/11/2022 2 08/11/2022 Books
    Dewey Decimal Classification     Premier University Department of Mathematics Library Premier University Department of Mathematics Library 23/10/2022 purchase 006.3/1 D325m 2019 26077 08/11/2022 3 08/11/2022 Books
    Dewey Decimal Classification     Premier University Department of Mathematics Library Premier University Department of Mathematics Library 23/10/2022 purchase 006.3/1 D325m 2019 26078 08/11/2022 4 08/11/2022 Books
    Dewey Decimal Classification     Premier University Department of Mathematics Library Premier University Department of Mathematics Library 23/10/2022 purchase 006.3/1 D325m 2019 26079 08/11/2022 5 08/11/2022 Books
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