國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Data mining for business analytics :...

Bruce, Peter C., (1953-)

Data mining for business analytics :concepts, techniques and applications in Python /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Data mining for business analytics :Galit Shmueli, Peter C. Bruce, Peter Gedeck, Nitin R. Patel.
其他題名:	concepts, techniques and applications in Python /
作者:	Shmueli, Galit,
其他作者:	Bruce, Peter C.,
面頁冊數:	xxix, 574 pages : illustrations (some color), color maps; 26cm.
標題:	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 /
LDR:02622nam a2200361 a 4500 001 570468
005 20200519125845.0
006 m |o d |
007 cr_|||||||||||
008 200824s2020 nju ob 001 0 eng
010 $a 2019025015
020 $a 9781119549864 $q (epub)
020 $a 9781119549857 $q (adobe pdf)
020 $z 9781119549840 $q (hardback) $c $134.95
025 2 7 $a cam 2200349 i 4500
035 $a 21402923
040 $a DLC $b eng $c DLC $e rda $d DLC
042 $a pcc
050 0 0 $a HF5548.2
082 0 0 $a 650.072/7 $2 23
100 1 $a Shmueli, Galit, $d 1971- $3 280847
245 1 0 $a Data mining for business analytics : $b concepts, techniques and applications in Python / $c Galit Shmueli, Peter C. Bruce, Peter Gedeck, Nitin R. Patel.
264 1 $a Hoboken, NJ : $b John Wiley & Sons, Inc., $c 2020.
300 $a xxix, 574 pages : $b illustrations (some color), color maps; $c 26cm.
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
504 $a Includes bibliographical references and index.
520 $a "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"-- $c Provided by publisher.
588 $a Description based on print version record and CIP data provided by publisher.
650 0 $a Business mathematics $x Computer programs. $3 857102
650 0 $a Business $x Data processing. $3 199085
650 0 $a Data mining. $3 184440
650 0 $a Python (Computer program language) $3 215247
700 1 $a Bruce, Peter C., $d 1953- $3 280846
700 1 $a Gedeck, Peter, $e author. $3 857101
700 1 $a Patel, Nitin R. $q (Nitin Ratilal) $3 443910
776 0 8 $i Print version: $a Shmueli, Galit, 1971- $t Data mining for business analytics $d Hoboken, NJ : John Wiley & Sons, Inc., 2020. $z 9781119549840 $w (DLC) 2019025014
906 $a 7 $b cbc $c orignew $d 1 $e ecip $f 20 $g y-gencatlg
925 0 $a acquire $e ecip ebook $x policy default
955 $a ecip ebook 2020-01-27 $f rl46 2020-05-19 book rec'd (TW Situational)
985 $a LC online resource $d 2020-01-27