In this chapter, we got an overview of what machine learning is and what some of its high-level tasks are. We also discussed the importance of Bayesian inference in machine learning, particularly in the context of how it can help to avoid important issues, such as model overfit and how to select optimum models. In the coming chapters, we will learn some of the Bayesian machine learning methods in detail.
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