Practical Data Science with R

This invaluable addition to any data scientist's library shows you how to apply the R programming language and useful statistical techniques to everyday business situations as well as how to effectively present results to audiences of all levels. To answer the ever-increasing demand for machine learning and analysis, this new edition boasts additional R tools, modeling techniques, and more. Practical Data Science with R, Second Edition takes a practice oriented approach to explaining basic principles in the ever-expanding field of data science. You'll jump right to real-world use cases as you apply the R programming language and statistical analysis techniques to carefully explained examples based in marketing, business intelligence, and decision support. Key features. Data science and statistical analysis for the business professional. Numerous instantly familiar real-world use cases. Keys to effective data presentations. Modeling and analysis techniques like boosting, regularized regression, and quadratic discriminant analysis. Audience. While some familiarity with basic statistics and R is assumed, this book is accessible to readers with or without a background in data science. About the technology. Business analysts and developers are increasingly collecting, curating, analyzing, and reporting on crucial business data. The R language and its associated tools provide a straightforward way to tackle day-to-day.