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Applied Analytics through Case Studies Using SAS and R

Implementing Predictive Models and Machine Learning Techniques

  • Book
  • © 2018

Overview

Authors:
  1. Deepti Gupta

    1. Boston, USA

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  • Practical and hands-on approach in building the predictive model and machine learning technique using SAS and R
  • Covers real world business case studies from 6 industrial domains
  • Application of analytical approach to industrial business problems

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Table of contents (7 chapters)

  1. Front Matter

    Pages i-xx
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  2. Data Analytics and Its Application in Various Industries

    • Deepti Gupta
    Pages 1-25

  3. Banking Case Study

    • Deepti Gupta
    Pages 27-95

  4. Retail Case Study

    • Deepti Gupta
    Pages 97-160

  5. Telecommunication Case Study

    • Deepti Gupta
    Pages 161-220

  6. Healthcare Case Study

    • Deepti Gupta
    Pages 221-275

  7. Airline Case Study

    • Deepti Gupta
    Pages 277-343

  8. FMCG Case Study

    • Deepti Gupta
    Pages 345-396

  9. Back Matter

    Pages 397-404
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Keywords

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. 


What You'll Learn  
  • Understand analytics and basic data concepts 
  • Use an analytical approach to solve Industrial business problems 
  • Build predictive model with machine learning techniques
  • Create and apply analytical strategies




Who This Book Is For



Data scientists, developers, statisticians, engineers, and research students with a great theoretical understanding of data and statistics who would like to enhance their skills by getting practical exposure in data modeling.

Authors and Affiliations

  • Boston, USA

    Deepti Gupta

About the author

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.

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