The temptation to learn neural nets "with" a programming language as opposed to math, is probably because programming is more fun. And the reason it is more fu

The temptation to learn neural nets "with" a programming language as opposed to math, is probably because programming is more fun. And the reason it is more fun is because you are getting instant feedback, you fix the error and get a dopamine kick when it passed that error and so forth. All the programmers here know exactly what I mean. The math, meanwhile, is harder because you might read description, stare at an equation. Hope that you "get" it. Then read the next statement, realize you might have misunderstood the previous one and so on. You don't get the same sense of progress, and one bit of confusion can throw you off track for a long time. One contribution would be teach the math in an environment that is like programming. I am not sure what this would look like, but you would learn how to back propagate the derivative through the network, minimizing error at each step and forward propagate the signal. It can't just be a visualization because the student won't engage with it in the same way as a system with negative and positive feedback.