I agree that ML and AI are applied math. It is a, duh, no-brainer. But you might want to revise this: > IMHO, might look at ML as based heavily on the Leo Bre

I agree that ML and AI are applied math. It is a, duh, no-brainer. But you might want to revise this: > IMHO, might look at ML as based heavily on the Leo Breiman work in random forests and classification and regression trees (CART). There is a whole lot more to ML than decision forests. We have talked about this before, I suggest that you get started with Vapnik's books. They are not light reading but I can promise you will enjoy them. No seriously, just get those books. In fact his main result is bigger than ML, its a non-asymptotic distribution independent _uniform_ law of large numbers. ML is now in, what can be described as, a post-Vapnik era, but for someone steeped in probability and functional analysis that is the place to start.