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Data mining for business analytics :...
~
Bruce, Peter C., (1953-)
Data mining for business analytics :concepts, techniques and applications in Python /
Record Type:
Language materials, printed : Monograph/item
Title/Author:
Data mining for business analytics :Galit Shmueli, Peter C. Bruce, Peter Gedeck, Nitin R. Patel.
Reminder of title:
concepts, techniques and applications in Python /
Author:
Shmueli, Galit,
other author:
Bruce, Peter C.,
Description:
xxix, 574 pages : illustrations (some color), color maps; 26cm.
Subject:
Business mathematicsComputer programs.
ISBN:
9781119549864
Data mining for business analytics :concepts, techniques and applications in Python /
Shmueli, Galit,1971-
Data mining for business analytics :
concepts, techniques and applications in Python /Galit Shmueli, Peter C. Bruce, Peter Gedeck, Nitin R. Patel. - xxix, 574 pages : illustrations (some color), color maps; 26cm.
Includes bibliographical references and index.
"This book supplies insightful, detailed guidance on fundamental data mining techniques. The book guides readers through the use of Python software for developing predictive models and techniques in order to describe and find patterns in data. The authors use interesting, real-world examples to build a theoretical and practical understanding of key data mining methods, with a focus on analytics rather than programming. The book includes discussions of Python subroutines, allowing readers to work hands-on with the provided data. Throughout the book, applications of the discussed topics focus on the business problem as motivation and avoid unnecessary statistical theory. Topics covered include time series, text mining, and dimension reduction. Each chapter concludes with exercises that allow readers to expand their comprehension of the presented material. Over a dozen cases that require use of the different data mining techniques are introduced, and a related Web site features over two dozen data sets, exercise solutions, PowerPoint slides, and case solutions"--
ISBN: 9781119549864
LCCN: 2019025015Subjects--Topical Terms:
857102
Business mathematics
--Computer programs.
LC Class. No.: HF5548.2
Dewey Class. No.: 650.072/7
Data mining for business analytics :concepts, techniques and applications in Python /
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concepts, techniques and applications in Python /
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Galit Shmueli, Peter C. Bruce, Peter Gedeck, Nitin R. Patel.
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Hoboken, NJ :
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John Wiley & Sons, Inc.,
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2020.
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xxix, 574 pages :
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"This book supplies insightful, detailed guidance on fundamental data mining techniques. The book guides readers through the use of Python software for developing predictive models and techniques in order to describe and find patterns in data. The authors use interesting, real-world examples to build a theoretical and practical understanding of key data mining methods, with a focus on analytics rather than programming. The book includes discussions of Python subroutines, allowing readers to work hands-on with the provided data. Throughout the book, applications of the discussed topics focus on the business problem as motivation and avoid unnecessary statistical theory. Topics covered include time series, text mining, and dimension reduction. Each chapter concludes with exercises that allow readers to expand their comprehension of the presented material. Over a dozen cases that require use of the different data mining techniques are introduced, and a related Web site features over two dozen data sets, exercise solutions, PowerPoint slides, and case solutions"--
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Provided by publisher.
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Description based on print version record and CIP data provided by publisher.
650
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Business mathematics
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857102
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Bruce, Peter C.,
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Gedeck, Peter,
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Shmueli, Galit, 1971-
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Data mining for business analytics
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Hoboken, NJ : John Wiley & Sons, Inc., 2020.
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LC online resource
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2020-01-27
based on 0 review(s)
ALL
西方語文圖書區(四樓)
Items
1 records • Pages 1 •
1
Inventory Number
Location Name
Item Class
Material type
Call number
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Loan Status
No. of reservations
Opac note
Attachments
320000724429
西方語文圖書區(四樓)
1圖書
一般圖書
HF5548.2 S558-1 2020
一般使用(Normal)
On shelf
0
1 records • Pages 1 •
1
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