Business analytics using R - a practical approach
Material type:
TextPublication details: Bangalore Apress 2022 Description: xvii, 279 pISBN: 9781484256770Subject(s): Management information systems | Business--Data processing | R (Computer program language) | Data mining | Programming languages (Electronic computers)DDC classification: 650.0285 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
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|---|
Book
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Indian Institute of Management LRC General Stacks | IT & Decisions Sciences | 650.0285 HOD (Browse shelf(Opens below)) | 1 | Available | 003903 |
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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