Difficulty Level
Intermediate
Completion Time
5h36m
Language
English
About Book
Who Is This Book For?
This book is for statisticians, analysts, and data scientists who want to build a Bayes-based system with R and implement it in their day-to-day models and projects. It is mainly intended for Data Scientists and Software Engineers who are involved in the development of Advanced Analytics applications. To understand this book, it would be useful if you have basic knowledge of probability theory and analytics and some familiarity with the programming language R.
Learning Bayesian Models with R
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 5h36m total length
Overview of Probability Theory
Setting up the R Environment
Introducing Bayesian Inference
Machine Learning using Bayesian Inference
Getting to know Regression Models
Introducing Classification Models
Models for Unsupervised Learning
Probabilistic Graphical Models- Bayesian Networks
Big Data and Bayesian Inference
Related Resources
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