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Mathematical analysis for machine le...

Simovici, Dan A.

Mathematical analysis for machine learning and data mining

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Mathematical analysis for machine learning and data miningDan 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 learningMathematics.
電子資源:	https://www.worldscientific.com/worldscibooks/10.1142/10702#t=toc
ISBN:	9789813229693$q(electronic bk.)

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: 9789813229693$q(electronic bk.)Subjects--Topical Terms:

840165
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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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 840165
650 0 $a Data mining $x Mathematics. $3 735581
650 0 $a Electronic books. $3 242495
856 4 0 $u https://www.worldscientific.com/worldscibooks/10.1142/10702#t=toc