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Data science for mathematicians /

Carter, Nathan C.,

Data science for mathematicians /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Data science for mathematicians /edited by Nathan Carter.
其他作者:	Carter, Nathan C.,
出版者:	Boca Raton, FL :CRC Press,2021.
面頁冊數:	xv, 528 p. :ill. ;25 cm
標題:	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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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.
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