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Data Science Using Oracle Data Miner...

Das, Sibanjan.

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Data Science Using Oracle Data Miner and Oracle R Enterprise = transform your business systems into an analytical powerhouse /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Data Science Using Oracle Data Miner and Oracle R Enterprise/ by Sibanjan Das.
Reminder of title:	transform your business systems into an analytical powerhouse /
Author:	Das, Sibanjan.
Published:	Berkeley, CA :Apress : : 2016.,
Description:	xxii, 289 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction Chapter 1 : Getting Started with Oracle Advanced Analytics -- Chapter 2 : Installation and Hello World -- Chapter 3: Clustering Methods -- Chapter 4: Association Rules -- Chapter 5: Regression Analysis -- Chapter 6: Classification Techniques -- Chapter 7: Advanced Topics -- Chapter 8: Solution Deployment.
Contained By:	Springer eBooks
Subject:	Data mining. -
Online resource:	http://dx.doi.org/10.1007/978-1-4842-2614-8
ISBN:	9781484226148

Data Science Using Oracle Data Miner and Oracle R Enterprise = transform your business systems into an analytical powerhouse /
Das, Sibanjan.

Data Science Using Oracle Data Miner and Oracle R Enterprisetransform your business systems into an analytical powerhouse /[electronic resource] :by Sibanjan Das. - Berkeley, CA :Apress :2016. - xxii, 289 p. :ill., digital ;24 cm.

Introduction Chapter 1 : Getting Started with Oracle Advanced Analytics -- Chapter 2 : Installation and Hello World -- Chapter 3: Clustering Methods -- Chapter 4: Association Rules -- Chapter 5: Regression Analysis -- Chapter 6: Classification Techniques -- Chapter 7: Advanced Topics -- Chapter 8: Solution Deployment.

Automate the predictive analytics process using Oracle Data Miner and Oracle R Enterprise. This book talks about how both these technologies can provide a framework for in-database predictive analytics. You'll see a unified architecture and embedded workflow to automate various analytics steps such as data preprocessing, model creation, and storing final model output to tables. You'll take a deep dive into various statistical models commonly used in businesses and how they can be automated for predictive analytics using various SQL, PLSQL, ORE, ODM, and native R packages. You'll get to know various options available in the ODM workflow for driving automation. Also, you'll get an understanding of various ways to integrate ODM packages, ORE, and native R packages using PLSQL for automating the processes.

ISBN: 9781484226148

Standard No.: 10.1007/978-1-4842-2614-8doiSubjects--Topical Terms:

562972
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Data Science Using Oracle Data Miner and Oracle R Enterprise = transform your business systems into an analytical powerhouse /
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505 0 $a Introduction Chapter 1 : Getting Started with Oracle Advanced Analytics -- Chapter 2 : Installation and Hello World -- Chapter 3: Clustering Methods -- Chapter 4: Association Rules -- Chapter 5: Regression Analysis -- Chapter 6: Classification Techniques -- Chapter 7: Advanced Topics -- Chapter 8: Solution Deployment.
520 $a Automate the predictive analytics process using Oracle Data Miner and Oracle R Enterprise. This book talks about how both these technologies can provide a framework for in-database predictive analytics. You'll see a unified architecture and embedded workflow to automate various analytics steps such as data preprocessing, model creation, and storing final model output to tables. You'll take a deep dive into various statistical models commonly used in businesses and how they can be automated for predictive analytics using various SQL, PLSQL, ORE, ODM, and native R packages. You'll get to know various options available in the ODM workflow for driving automation. Also, you'll get an understanding of various ways to integrate ODM packages, ORE, and native R packages using PLSQL for automating the processes.
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