A Gentle Introduction to Bayes’ Theorem for Machine Learning
change my mind: bayes in practice is just a way to regularize your model and the language of bayes makes it seem principled but really you could use literally any regularizer and it would work almost just as well. i believe this because ultimately you're always going to minimize loglikelihood anyway (and so the prior becomes the regularization term).