[psv1]

> If you like books and you want to deeply understand ML techniques I'd suggest jumping straight into "Introduction to Statistical Learning" and only learning calculus/stats/matrix methods (linear algebra) as you need them (you really don't need much from them in practice).

This doesn't work. ISL is good, but it aims to be accessible by excluding most of the math. So if you go over it, you'll neither "deeply understand ML techniques", nor will you encounter enough math that you can learn along the way as you suggest.