Bayesian Reasoning and Machine Learning by David Barber

Bayesian Reasoning and Machine Learning is a thorough open-source educational textbook and resource by David Barber that provides in-depth coverage of probabilistic machine learning methods grounded in Bayesian theory. The material serves as both a theoretical foundation and practical guide for understanding how Bayesian approaches can be applied to complex machine learning problems, from classification and regression to latent variable models and deep learning. This resource is designed for advanced students, researchers, and practitioners who want to develop a rigorous understanding of the mathematical principles underlying modern machine learning systems. The freely available PDF format makes it accessible to anyone seeking to connects classical statistics and contemporary machine learning applications.