Introduction to Statistical Learning
https://faculty.marshall.usc.edu/gareth-james/ISL/
Elements of Statistical Learning
https://web.stanford.edu/~hastie/ElemStatLearn/
Machine Learning: A Probabilistic Perspective
https://faculty.marshall.usc.edu/gareth-james/ISL/
Elements of Statistical Learning
https://web.stanford.edu/~hastie/ElemStatLearn/
Machine Learning: A Probabilistic Perspective
Especially the first 2 are rather the standard "intro to ML textbooks", with a frequentist focus (ISL may even have zero Bayesian stuff - Naive Bayes is not "Bayesian" – while ESL still has maybe 10% bayesian content if that).
Instead, I would suggest the following for learning Bayesian methods, especially given the HN crowd: https://github.com/CamDavidsonPilon/Probabilistic-Programmin...