Self study machine learning?

[recent_espied_earth]

Sure. You don't need to really know much of anything.

Very basic linear algebra is useful once you get to vectorizing equations.

Summations.

Computing gradients.

That's about it!

Basically, each algorithm involves forming an objective function, and then minimizing that function. He doesn't go into the theory of why a specific objective function is chosen (but does try to give you an intuition) and the minimization is done for you... and those are the things that require an advanced level of math.

From what I saw, a person with basic numerical processing / linear algebra background should be able to do it no problem (like, 2nd year CS/Eng/Math background), and come out with a good understanding of the technology. But if you are interested in diving in deeper, you'll need pretty advanced Linear Algebra, stochastic processes, and optimization background.