In this chapter, you were introduced to the R environment. After reading through this chapter, you learned how to import data into R, make a selection of subsets of data for their analysis, and write simple R programs using functions and control structures. Also, you should now be familiar with the graphical capabilities of R and some advanced capabilities, such as loop functions. In the next chapter, we will begin the central theme of this book, Bayesian inference.
Learning Bayesian Models with R
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Learning Bayesian Models with R
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Overview of this book
Table of Contents (16 chapters)
Learning Bayesian Models with R
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Free Chapter
Introducing the Probability Theory
The R Environment
Introducing Bayesian Inference
Machine Learning Using Bayesian Inference
Bayesian Regression Models
Bayesian Classification Models
Bayesian Models for Unsupervised Learning
Bayesian Neural Networks
Bayesian Modeling at Big Data Scale
Index
Customer Reviews