Fundamentals of ML&AI

Hey guys, I want to revise my ML & DL concepts and would like to know if anyone knows good references/sources to revisit the concepts I want to cover the algorithms in fundamental depth rather than just application of models ( ex : difference between gradient descent / ols regressions When to use beta in classifications when looking at f score etc. what is the difference between acf/pacf in time series

Can someone suggest good sources where I can go through such concepts in depth? )