Predictive Analytics for Data Driven Decision Making – Tools and Techniques for Solving Real World Problems

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Series
: Research Methodology and Data Analysis
BISAC: COM021030
DOI: https://doi.org/10.52305/RZBM7280

Predictive analytics is an evolving field and has applications across all domains and sectors. This book will introduce to the reader the concept of predictive analytics and cover in detail the predictive analytic models, tools and techniques involved. The book will also cover the applications of predictive analytics in various domains including health care, banking, agriculture, retailing, sports and industries using smart grid and industrial drivers with real world scenarios. This book covers performance improvement and enhancement techniques with the aid of intelligent predictive analytical algorithms to predict future patterns. This would be a handy guide covering all steps from identification of the problem, preparing the data, model building and recommending solutions. Hence, the readers can experience the various types of performance improvement techniques and implement them in their specific domain.

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Table of Contents

Preface

Book Description

Acknowledgments

About the Authors

Chapter 1. Introduction to Predictive Analytics

Chapter 2. Predictive Analytics Modeling

Chapter 3. Predictive Analytics Tools and Techniques

Chapter 4. Big Data and Internet of Things

Chapter 5. Predictive Analytics in Smart Grid

Chapter 6. Predictive Analytics in Industrial Drives

Chapter 7. Predictive Analytics in Mitigating Power Quality Issues

Chapter 8. Predictive Analytics in Healthcare

Chapter 9. Predictive Analytics in Agriculture

Chapter 10. Predictive Analytics in Banking Sector

Chapter 11. Predictive Analytics in Retailing

Chapter 12. Predictive Analytics in Sports Management

Index


Author’s ORCID iD

L. Ashok Kumar: https://orcid.org/0000-0001-5962-2961
R. Sujatha: https://orcid.org/0000-0002-5622-8392
B. Uma Maheswari: https://orcid.org/0000-0002-7487-7783

Additional information

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