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Mathematical analysis for machine le...

Simovici, Dan A.

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Mathematical analysis for machine learning and data mining

Record Type:	Electronic resources : Monograph/item
Title/Author:	Mathematical analysis for machine learning and data mining/ Dan Simovici.
Author:	Simovici, Dan A.
Published:	Singapore :World Scientific, : c2018.,
Description:	1 online resource (985 p.) :ill.
Subject:	0Machine learning - Mathematics. -
Online resource:	https://www.worldscientific.com/worldscibooks/10.1142/10702#t=toc
ISBN:	9789813229693

Mathematical analysis for machine learning and data mining
Simovici, Dan A.

Mathematical analysis for machine learning and data mining[electronic resource] /Dan Simovici. - 1st ed. - Singapore :World Scientific,c2018. - 1 online resource (985 p.) :ill.

Includes bibliographical references (p. 949-955) and index.

"This compendium provides a self-contained introduction to mathematical analysis in the field of machine learning and data mining. The mathematical analysis component of the typical mathematical curriculum for computer science students omits these very important ideas and techniques which are indispensable for approaching specialized area of machine learning centered around optimization such as support vector machines, neural networks, various types of regression, feature selection, and clustering. The book is of special interest to researchers and graduate students who will benefit from these application areas discussed in the book."--Publisher's website.

Electronic reproduction.
Singapore :
World Scientific,
[2018]

Mode of access: World Wide Web.

ISBN: 9789813229693Subjects--Topical Terms:

3391376
0Machine learning
--Mathematics.

LC Class. No.: Q325.5 / .S57 2018

Dewey Class. No.: 006.3/101515

Mathematical analysis for machine learning and data mining
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020 $z 9789813229686 $q (hbk.)
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040 $a WSPC $b eng $c WSPC
041 0 $a eng
050 0 4 $a Q325.5 $b .S57 2018
082 0 4 $a 006.3/101515 $2 23
100 1 $a Simovici, Dan A. $3 908207
245 1 0 $a Mathematical analysis for machine learning and data mining $h [electronic resource] / $c Dan Simovici.
250 $a 1st ed.
260 $a Singapore : $b World Scientific, $c c2018.
300 $a 1 online resource (985 p.) : $b ill.
504 $a Includes bibliographical references (p. 949-955) and index.
520 $a "This compendium provides a self-contained introduction to mathematical analysis in the field of machine learning and data mining. The mathematical analysis component of the typical mathematical curriculum for computer science students omits these very important ideas and techniques which are indispensable for approaching specialized area of machine learning centered around optimization such as support vector machines, neural networks, various types of regression, feature selection, and clustering. The book is of special interest to researchers and graduate students who will benefit from these application areas discussed in the book."--Publisher's website.
533 $a Electronic reproduction. $b Singapore : $c World Scientific, $d [2018]
538 $a Mode of access: World Wide Web.
588 $a Description based on online resource; title from PDF title page (viewed May 17, 2018)
650 0 $a 0Machine learning $x Mathematics. $3 3391376
650 0 $a Data mining $x Mathematics. $3 2144379
650 0 $a Electronic books. $3 855788
856 4 0 $u https://www.worldscientific.com/worldscibooks/10.1142/10702#t=toc