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Business analytics using R - a practical approach

Author: Umesh Hodeghatta Rao; Umesh Nayak
Publisher: [United States] : Apress, New York, NY : Distributed to the Book trade worldwide by Springer 2017. ©2017
Edition/Format:   eBook : Document : EnglishView all editions and formats
Summary:
Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization. This book explains practical business analytics through examples, covers the steps involved in using it correctly, and shows you the context in which a particular technique does not make sense. Further, Practical Business Analytics using  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Hodeghatta, Umesh R.
Business analytics using R - A practical approach.
[Berkeley, California?] : Apress, 2017
(OCoLC)961002813
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Umesh Hodeghatta Rao; Umesh Nayak
ISBN: 9781484225141 1484225147
OCLC Number: 967342635
Description: 1 online resource (xvii, 280 pages) : illustrations
Contents: Overview of business analytics --
Introduction to R --
R for data analysis --
Introduction to descriptive analytics --
Business analytics process and data exploration --
Supervised machine learning : classification --
Unsupervised machine learning --
Simple linear regression --
Multiple linear regression --
Logistic regression --
Big data analysis : introduction and future trends.
Responsibility: Dr. Umesh R. Hodeghatta, Umesha Nayak.

Abstract:

Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization. This book explains practical business analytics through examples, covers the steps involved in using it correctly, and shows you the context in which a particular technique does not make sense. Further, Practical Business Analytics using R helps you understand specific issues faced by organizations and how the solutions to these issues can be facilitated by business analytics. This book will discuss and explore the following through examples and case studies: An introduction to R: data management and R functions The architecture, framework, and life cycle of a business analytics project Descriptive analytics using R: descriptive statistics and data cleaning Data mining: classification, association rules, and clustering Predictive analytics: simple regression, multiple regression, and logistic regression This book includes case studies on important business analytic techniques, such as classification, association, clustering, and regression. The R language is the statistical tool used to demonstrate the concepts throughout the book. You will:? Write R programs to handle data? Build analytical models and draw useful inferences from them? Discover the basic concepts of data mining and machine learning? Carry out predictive modeling? Define a business issue as an analytical problem.

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