Business analytics using R - a practical approach

By:

Hodeghatta, Umesh R

Contributor(s):

Umesha, Nayak

Material type: Text

TextPublication details: Apress Bangalore 2022Description: xvii, 279 pISBN:

9781484256770

Subject(s):

DDC classification:

650.0285 HOD

Summary: The book covers both descriptive analytics and predictive analytics. It also discusses business value and how analytics is linked to statistics, machine learning, and artificial intelligence. Most of the books in the market cover only statistics or regression whereas we cover complete analytics and its life cycle This book explains the concepts backed by examples and case studies which are easy to understand and follow This book offers the appropriate mix of theory and practice with relevant and useful examples

List(s) this item appears in: IT & Decision Sciences | HR & OB

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	IT & Decisions Sciences	650.0285 HOD (Browse shelf(Opens below))	1	Available		003903

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Overview of Business Analytics
Umesh R. Hodeghatta, Umesh Nayak
Pages 1-15
Introduction to R
Umesh R. Hodeghatta, Umesh Nayak
Pages 17-36
R for Data Analysis
Umesh R. Hodeghatta, Umesh Nayak
Pages 37-58
Introduction to descriptive analytics
Umesh R. Hodeghatta, Umesh Nayak
Pages 59-89
Business Analytics Process and Data Exploration
Umesh R. Hodeghatta, Umesh Nayak
Pages 91-130
Supervised Machine Learning—Classification
Umesh R. Hodeghatta, Umesh Nayak
Pages 131-160
Unsupervised Machine Learning
Umesh R. Hodeghatta, Umesh Nayak
Pages 161-186
Simple Linear Regression
Umesh R. Hodeghatta, Umesh Nayak
Pages 187-205
Multiple Linear Regression
Umesh R. Hodeghatta, Umesh Nayak
Pages 207-231
Logistic Regression
Umesh R. Hodeghatta, Umesh Nayak
Pages 233-255
Big Data Analysis—Introduction and Future Trends

The book covers both descriptive analytics and predictive analytics. It also discusses business value and how analytics is linked to statistics, machine learning, and artificial intelligence. Most of the books in the market cover only statistics or regression whereas we cover complete analytics and its life cycle

This book explains the concepts backed by examples and case studies which are easy to understand and follow

This book offers the appropriate mix of theory and practice with relevant and useful examples

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