I am working through Google's machine learning crash course.

https://developers.google.com/machine-learning/crash-course/...

Tensorflow sprays a lot of calculus. The idea is that all your known quantities ("features") become terms in an n-dimensional polynomial. The act of "training the model" is finding minima by traversing the negative gradient (the terms of the partial derivatives of any point when projected as a vector at that point).

I'm glad I had calc 3, even if that was only 3-dimensional.