Mathematical analysis for machine learning and data mining

By:

Simovici, Dan

Material type: Text

TextPublication details: London World Scientific 2020Description: 968 pISBN:

9780000988898

Subject(s):

DDC classification:

006.31015 SIM

Summary: 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.

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Item type	Current library	Call number	Status	Date due	Barcode	Item holds
Books	Gandhi Smriti Library	006.31015 SIM (Browse shelf(Opens below))	Available		179509
Books	Gandhi Smriti Library	006.31015 SIM (Browse shelf(Opens below))	Available		163064

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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.

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