A little bit of A and B. You can do a lot with very little math beyond linear algebra, calculus, and undergraduate probability, and that knowledge is mainly there to provide intuition and formalize the problem that you’re solving a bit. You also churn out results (including very impressive ones) without doing any math.

A result of the above is that people are empirically demonstrating new problems and solving them very quickly — much more quickly than people can come up with theoretical results explaining why they work. The theory is harder to come by for a few reasons, but many of the successful examples of deep learning don’t fit nicely into older frameworks from, e.g., statistics and optimal control, to explain them well.