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Data science for mathematicians /

Carter, Nathan C.,

Data science for mathematicians /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Data science for mathematicians /edited by Nathan Carter.
other author:	Carter, Nathan C.,
Published:	Boca Raton, FL :CRC Press,2021.
Description:	xv, 528 p. :ill. ;25 cm
Subject:	Big dataMathematics.
ISBN:	9780367027056 :

Data science for mathematicians /
Data science for mathematicians /edited by Nathan Carter. - 1st ed. - Boca Raton, FL :CRC Press,2021. - xv, 528 p. :ill. ;25 cm - CRC Press/Chapman and Hall handbooks in mathematics series. - CRC Press/Chapman and Hall handbooks in mathematics series..

Includes bibliographical references (p. 475-514) and index.

Programming with data / Sean Raleigh -- Linear algebra / Jeffery Leader -- Basic statistics / David White -- Clustering / Amy S. Wagaman -- Operations research / Alice Paul and Susan Martonosi -- Dimensionality reduction / Sofya Chepushtanova, Elin Farnell, Eric Kehoe, Michael Kirby, and Henry Kvinge -- Machine learning / Mahesh Agarwal, Nathan Carter, and David Oury -- Deep learning / Samuel S. Watson -- Topological data analysis / Henry Adams, Johnathan Bush, Joshua Mirth.

"Mathematicians have skills that, if deepened in the right ways, would enable them to use data to answer questions important to them and others, and report those answers in compelling ways. Data science combines parts of mathematics, statistics, computer science. Gaining such power and the ability to teach has reinvigorated the careers of mathematicians. This handbook will assist mathematicians to better understand the opportunities presented by data science"--

ISBN: 9780367027056 :NT$4902

LCCN: 2020011719Subjects--Topical Terms:

721851
Big data
--Mathematics.

LC Class. No.: QA300 / D232 2021

Dewey Class. No.: 515

Data science for mathematicians /
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245 0 0 $a Data science for mathematicians / $c edited by Nathan Carter.
250 $a 1st ed.
260 $a Boca Raton, FL : $b CRC Press, $c 2021.
300 $a xv, 528 p. : $b ill. ; $c 25 cm
490 1 $a CRC Press/Chapman and Hall handbooks in mathematics series
504 $a Includes bibliographical references (p. 475-514) and index.
505 0 $a Programming with data / Sean Raleigh -- Linear algebra / Jeffery Leader -- Basic statistics / David White -- Clustering / Amy S. Wagaman -- Operations research / Alice Paul and Susan Martonosi -- Dimensionality reduction / Sofya Chepushtanova, Elin Farnell, Eric Kehoe, Michael Kirby, and Henry Kvinge -- Machine learning / Mahesh Agarwal, Nathan Carter, and David Oury -- Deep learning / Samuel S. Watson -- Topological data analysis / Henry Adams, Johnathan Bush, Joshua Mirth.
520 $a "Mathematicians have skills that, if deepened in the right ways, would enable them to use data to answer questions important to them and others, and report those answers in compelling ways. Data science combines parts of mathematics, statistics, computer science. Gaining such power and the ability to teach has reinvigorated the careers of mathematicians. This handbook will assist mathematicians to better understand the opportunities presented by data science"-- $c Provided by publisher.
650 0 $a Big data $x Mathematics. $3 721851
650 0 $a Data mining. $3 184440
650 0 $a Mathematical analysis. $3 186133
650 0 $a Mathematical statistics. $3 181877
700 1 $a Carter, Nathan C., $e editor. $3 885134
830 0 $a CRC Press/Chapman and Hall handbooks in mathematics series. $3 885135