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
- Book Title Applied Analytics through Case Studies Using SAS and R
- Book Subtitle Implementing Predictive Models and Machine Learning Techniques
- DOI https://doi.org/10.1007/978-1-4842-3525-6
- Copyright Information Deepti Gupta 2018
- Publisher Name Apress, Berkeley, CA
- eBook Packages Professional and Applied Computing Professional and Applied Computing (R0)
- Softcover ISBN 978-1-4842-3524-9
- eBook ISBN 978-1-4842-3525-6
- Edition Number 1
- Number of Pages XX, 404
- Number of Illustrations 99 b/w illustrations, 0 illustrations in colour
Probability and Statistics in Computer Science
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