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

Applied analytics through case studi...

Gupta, Deepti.

Applied analytics through case studies using SAS and Rimplementing predictive models and machine learning techniques /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Applied analytics through case studies using SAS and Rby Deepti Gupta.
其他題名:	implementing predictive models and machine learning techniques /
作者:	Gupta, Deepti.
出版者:	Berkeley, CA :Apress :2018.
面頁冊數:	xx, 404 p. :digital ;24 cm.
Contained By:	Springer eBooks
標題:	Business enterprisesCase studies.Evaluation
電子資源:	http://dx.doi.org/10.1007/978-1-4842-3525-6
ISBN:	9781484235256$q(electronic bk.)

Applied analytics through case studies using SAS and Rimplementing predictive models and machine learning techniques /
Gupta, Deepti.

Applied analytics through case studies using SAS and Rimplementing predictive models and machine learning techniques /[electronic resource] :by Deepti Gupta. - Berkeley, CA :Apress :2018. - xx, 404 p. :digital ;24 cm.

Chapter 1: Role of Analytics in Various Industries -- Chapter 2: Banking Case Study with Analytical Solutions -- Chapter 3: Retail Case Study with Analytical Solutions -- Chapter 4: Telecommunication Case Study with Analytical Solutions -- Chapter 5: Healthcare Case Study with Analytical Solutions -- Chapter 6: Airline Case Study with Analytical Solutions -- Chapter 7: FMCG Case Study with Analytical Solutions.

Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language. This book is ideal for those who are well-versed in writing code and have a basic understanding of statistics, but have limited experience in implementing predictive models and machine learning techniques for analyzing real world data. The most challenging part of solving industrial business problems is the practical and hands-on knowledge of building and deploying advanced predictive models and machine learning algorithms. Applied Analytics through Case Studies Using SAS and R is your answer to solving these business problems by sharpening your analytical skills.

ISBN: 9781484235256$q(electronic bk.)

Standard No.: 10.1007/978-1-4842-3525-6doiSubjects--Uniform Titles:

SAS (Computer file)
Subjects--Topical Terms:

538221
Business enterprises
--Evaluation--Case studies.

LC Class. No.: HB3730 / .G878 2018

Dewey Class. No.: 338.7

Applied analytics through case studies using SAS and Rimplementing predictive models and machine learning techniques /
LDR:02161nmm a2200301 a 4500 001 543269
003 DE-He213
005 20190213155833.0
006 m d
007 cr nn 008maaau
008 190411s2018 cau s 0 eng d
020 $a 9781484235256$q(electronic bk.)
020 $a 9781484235249$q(paper)
021 2 5 $a nam a2200289 a 4500
024 7 $a 10.1007/978-1-4842-3525-6 $2 doi
035 $a 978-1-4842-3525-6
040 $a GP $c GP
041 0 $a eng
050 4 $a HB3730 $b .G878 2018
082 0 4 $a 338.7 $2 23
090 $a HB3730 $b .G977 2018
100 1 $a Gupta, Deepti. $3 792950
245 1 0 $a Applied analytics through case studies using SAS and R $h [electronic resource] : $b implementing predictive models and machine learning techniques / $c by Deepti Gupta.
260 $a Berkeley, CA : $b Apress : $b Imprint: Apress, $c 2018.
300 $a xx, 404 p. : $b digital ; $c 24 cm.
505 0 $a Chapter 1: Role of Analytics in Various Industries -- Chapter 2: Banking Case Study with Analytical Solutions -- Chapter 3: Retail Case Study with Analytical Solutions -- Chapter 4: Telecommunication Case Study with Analytical Solutions -- Chapter 5: Healthcare Case Study with Analytical Solutions -- Chapter 6: Airline Case Study with Analytical Solutions -- Chapter 7: FMCG Case Study with Analytical Solutions.
520 $a Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language. This book is ideal for those who are well-versed in writing code and have a basic understanding of statistics, but have limited experience in implementing predictive models and machine learning techniques for analyzing real world data. The most challenging part of solving industrial business problems is the practical and hands-on knowledge of building and deploying advanced predictive models and machine learning algorithms. Applied Analytics through Case Studies Using SAS and R is your answer to solving these business problems by sharpening your analytical skills.
630 0 0 $a SAS (Computer file) $3 185323
650 0 $a Business enterprises $x Evaluation $v Case studies. $3 538221
650 0 $a Machine learning. $3 188639
650 0 $a R (Computer program language) $3 210846
650 1 4 $a Computer Science. $3 212513
650 2 4 $a Big Data. $3 760530
650 2 4 $a Open Source. $3 758930
650 2 4 $a Probability and Statistics in Computer Science. $3 274053
650 2 4 $a Business Mathematics. $3 696407
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-1-4842-3525-6
950 $a Professional and Applied Computing (Springer-12059)