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Applied Analytics through Case Studies Using SAS and R

Implementing Predictive Models and Machine Learning Techniques

Authors: Gupta, Deepti

  • 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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Buy this book

eBook $29.99
price for USA (gross)
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: September 18, 2018
  • ISBN 978-1-4842-3525-6
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Softcover $37.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: September 18, 2018
  • ISBN 978-1-4842-3524-9
  • Free shipping for individuals worldwide
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.

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.

Buy this book

eBook $29.99
price for USA (gross)
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: September 18, 2018
  • ISBN 978-1-4842-3525-6
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Softcover $37.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: September 18, 2018
  • ISBN 978-1-4842-3524-9
  • Free shipping for individuals worldwide

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Bibliographic Information

Bibliographic Information
Book Title
Applied Analytics through Case Studies Using SAS and R
Book Subtitle
Implementing Predictive Models and Machine Learning Techniques
Authors
Copyright
2018
Publisher
Apress
Copyright Holder
Deepti Gupta
Distribution Rights
Standard Apress distribution
eBook ISBN
978-1-4842-3525-6
DOI
10.1007/978-1-4842-3525-6
Softcover ISBN
978-1-4842-3524-9
Edition Number
1
Number of Pages
IV, 232
Number of Illustrations and Tables
10 b/w illustrations, 88 illustrations in colour
Topics