Christopher Bishop’s "Pattern Recognition and Machine Learning" (2006) serves as a foundational text for the Bayesian approach to machine learning, emphasizing probability theory over simple engineering heuristics. It offers a rigorous mathematical framework, particularly in its treatment of linear models, graphical models, and approximate inference methods like Variational Bayes. AI responses may include mistakes. Learn more