**Dr. Hari M. Koduvely** is an experienced data scientist working at the Samsung R&D Institute in Bangalore, India. He has a PhD in statistical physics from the Tata Institute of Fundamental Research, Mumbai, India, and post-doctoral experience from the Weizmann Institute, Israel, and Georgia Tech, USA. Prior to joining Samsung, the author has worked for Amazon and Infosys Technologies, developing machine learning-based applications for their products and platforms. He also has several publications on Bayesian inference and its applications in areas such as recommendation systems and predictive health monitoring. His current interest is in developing large-scale machine learning methods, particularly for natural language understanding.

#### 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