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Mathematical analysis for machine le...

Simovici, Dan A.

Mathematical analysis for machine learning and data mining[electronic resource] /

紀錄類型:	書目-電子資源 : Monograph/item
杜威分類號:	006.3/101515
書名/作者:	Mathematical analysis for machine learning and data mining/ Dan Simovici.
作者:	Simovici, Dan A.
出版者:	Singapore : : World Scientific,, c2018.
面頁冊數:	1 online resource (985 p.) : : ill.
標題:	0Machine learning - Mathematics.
標題:	Data mining - Mathematics.
標題:	Electronic books.
ISBN:	9789813229693
書目註:	Includes bibliographical references (p. 949-955) and index.
摘要、提要註:	"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.
電子資源:	https://www.worldscientific.com/worldscibooks/10.1142/10702#t=toc

Mathematical analysis for machine learning and data mining[electronic resource] /
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:

709890
0Machine learning
--Mathematics.

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

Dewey Class. No.: 006.3/101515

Mathematical analysis for machine learning and data mining[electronic resource] /
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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 487299
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 709890
650 0 $a Data mining $x Mathematics. $3 709891
650 0 $a Electronic books. $2 local $3 376747
856 4 0 $u https://www.worldscientific.com/worldscibooks/10.1142/10702#t=toc

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