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Author Rao, Umesh Hodeghatta, author.

Title Business analytics using R - a practical approach / Dr. Umesh R. Hodeghatta, Umesha Nayak.

Publication Info. [United States] : Apress, 2017.
New York, NY : Distributed to the Book trade worldwide by Springer
2017

Copies

Location Call No. OPAC Message Status
 Axe Books 24x7 IT E-Book  Electronic Book    ---  Available
Description 1 online resource (xvii, 280 pages) : illustrations
text txt rdacontent
computer c rdamedia
online resource cr rdacarrier
Bibliography Includes bibliographical references and index.
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.
Note Print version record.
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 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.
Subject Business -- Data processing.
Management information systems.
R (Computer program language)
BUSINESS & ECONOMICS -- Management.
BUSINESS & ECONOMICS -- Reference.
BUSINESS & ECONOMICS -- Skills.
Business -- Data processing. (OCoLC)fst00842293
Management information systems. (OCoLC)fst01007271
R (Computer program language) (OCoLC)fst01086207
Computer programming / software development.
Programming & scripting languages: general.
Data mining.
Information retrieval.
Maths for computer scientists.
Databases.
Genre/Form Electronic books.
Added Author Nayak, Umesh, author.
Other Form: Print version: Hodeghatta, Umesh R. Business analytics using R - A practical approach. [Berkeley, California?] : Apress, 2017 1484225139 (OCoLC)961002813
ISBN 9781484225141 (electronic bk.)
1484225147 (electronic bk.)
9781484225134 (pbk.)
1484225139 (pbk.)
Standard No. CHDSB 006710583
CHVBK 486373762
AU@ 000059505546
UKMGB 019139934

 
    
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