Applied Analytics through Case Studies Using SAS and R Implementing Predictive Models and Machine Learning Techniques /

• Main Author: Gupta, Deepti (Author, http://id.loc.gov/vocabulary/relators/aut)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Berkeley, CA : Apress : Imprint: Apress, 2018.
• Edition: 1st ed. 2018.
• Subjects: Big data.; Open source software.; Computer programming.; Mathematical statistics.; Business mathematics.; Big Data.; Open Source.; Probability and Statistics in Computer Science.; Business Mathematics.
• Physical Description: XX, 404 p. 99 illus. online resource.
• ISBN: 9781484235256
• DOI: 10.1007/978-1-4842-3525-6

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. .