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Predictive analytics for dummies /

Bari, Anasse,

Predictive analytics for dummies /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Predictive analytics for dummies /by Anasse Bari, Mohamed Chaouchi, and Tommy Jung.
作者:	Bari, Anasse,
其他作者:	Chaouchi, Mohamed,
出版者:	Hoboken, NJ :John Wiley & Sons, Inc.,c2014.
面頁冊數:	xii, 344 p. :ill. ;24 cm.
附註:	"Business data marketing"--Back cover.
附註:	"Learn to: Analyze structured and unstructured data ; Use algorithms and data analysis techniques ; Build clustering, classificaion and statistical models ; Apply predictive analytics to your website and marketing efforts"--Cover.
附註:	Includes index.
標題:	Data mining.
ISBN:	1118728963 (pbk.)

Predictive analytics for dummies /
Bari, Anasse,

Predictive analytics for dummies /by Anasse Bari, Mohamed Chaouchi, and Tommy Jung. - Hoboken, NJ :John Wiley & Sons, Inc.,c2014. - xii, 344 p. :ill. ;24 cm. - --For dummies. - --For dummies..

"Business data marketing"--Back cover.

Getting started with predictive analytics. Entering the arena ;Introduction. --

Predict the future! This practical guide will help you use Big Data and technology to discover real-world insights, define projects, and help you create goals.

ISBN: 1118728963 (pbk.)

LCCN: 2013954216

Nat. Bib. No.: GBB410562bnb

Nat. Bib. Agency Control No.: 016612323UkSubjects--Topical Terms:

184440
Data mining.

LC Class. No.: HD30.25 / .B3645 2014

Dewey Class. No.: 658.056312

Predictive analytics for dummies /
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245 1 0 $a Predictive analytics for dummies / $c by Anasse Bari, Mohamed Chaouchi, and Tommy Jung.
260 $a Hoboken, NJ : $b John Wiley & Sons, Inc., $c c2014.
300 $a xii, 344 p. : $b ill. ; $c 24 cm.
490 1 $a --For dummies
500 $a "Business data marketing"--Back cover.
500 $a "Learn to: Analyze structured and unstructured data ; Use algorithms and data analysis techniques ; Build clustering, classificaion and statistical models ; Apply predictive analytics to your website and marketing efforts"--Cover.
500 $a Includes index.
505 0 0 $g Introduction. -- $g pt. 1. $t Getting started with predictive analytics. Entering the arena ; $t Predictive analytics in the wild ; $t Exploring your data types and associated techniques ; $t Complexities of data -- $g pt. 2. $t Incorporating algorithms in your models. Applying models ; $t Identifying similarities in data ; $t Predicting the future using data classification -- $g pt. 3. $t Developing a roadmap. Convincing your management to adopt predictive analytics ; $t Preparing data ; $t Building a predictive model ; $t Visualization of analytical results -- $g pt. 4. $t Programming predictive analytics. Creating basic prediction examples ; $t Creating basic examples of unsupervised predictions ; $t Predictive modeling with R ; $t Avoiding analysis traps ; $t Targeting big data -- $g pt. 5. The $t part of tens. $t Ten reasons to implement predictive analytics ; $t Ten steps to build a predictive analytic model.
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650 0 $a Data mining. $3 184440
650 0 $a Management $x Data processing. $3 219227
650 0 $a Management $x Mathematical models. $3 184128
700 1 $a Chaouchi, Mohamed, $e author. $3 735658
700 1 $a Jung, Tommy, $e author. $3 735659
830 0 $a --For dummies. $3 378549