Bayesian Statistical Methods: With Applications to Machine Learning (Chapman & Hall/CRC Texts in Statistical Science)

Bayesian Statistical Methods: With Applications to Machine Learning provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis.Compared to others, this book is more focused on Bayesian methods applied routinely in practice, including multiple linear regression, mixed effects models and generalized linear models.This second edition includes a new chapter on Bayesian machine learning methods to handle large and complex datasets and several new applications to illustrate the benefits of the Bayesian approach in terms of uncertainty quantification.Readers familiar with only introductory statistics will find this book accessible, as it includes many worked examples with complete R code, and comparisons are presented with analogous frequentist procedures.The book can be used as a one-semester course for advanced undergraduate and graduate students and can be used in courses comprising undergraduate statistics majors, as well as non-statisti