© 2018

Applied Analytics through Case Studies Using SAS and R

Implementing Predictive Models and Machine Learning Techniques


Table of contents

  1. Front Matter
    Pages i-xx
  2. Deepti Gupta
    Pages 27-95
  3. Deepti Gupta
    Pages 97-160
  4. Deepti Gupta
    Pages 161-220
  5. Deepti Gupta
    Pages 221-275
  6. Deepti Gupta
    Pages 277-343
  7. Deepti Gupta
    Pages 345-396
  8. Back Matter
    Pages 397-404

About this book


Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language.  

This book is ideal for those who are well-versed in writing code and have a basic understanding of statistics, but have limited experience in implementing predictive models and machine learning techniques for analyzing real world data.  The most challenging part of solving industrial business problems is the practical and hands-on knowledge of building and deploying advanced predictive models and machine learning algorithms. 

Applied Analytics through Case Studies Using SAS and R is your answer to solving these business problems by sharpening your analytical skills. 


Business Analytics R SAS Machine Learning Telecom Healthcare Banking FMCG

Authors and affiliations

  1. 1.BostonUSA

About the authors

Deepti Gupta completed her MBA in Finance and PGPM in operation research in 2010. She has worked with KPMG and IBM private limited as Data Scientist and is currently working as a data science freelancer. Deepti has extensive experience in predictive modeling and machine learning with an expertise in SAS and R. Deepti has developed data science courses, delivered data science trainings, and conducted workshops for both corporate and academic institutions. She has written multiple blogs and white papers. Deepti has a passion for mentoring budding data scientists.

Bibliographic information

Industry Sectors
IT & Software
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Finance, Business & Banking