First, I agree with both (1) the encouragement of who might have been a student "wanting to apply a neural network to *something*," and also (2) the concern in the workplace re the willingness to advocate/use machine learning techniques when other approaches are available... that are "simpler," or even more efficient, or provably optimal, etc. I qualify "simpler" because I think the problem is almost the reverse-- I see analysts willing to take the machine learning black box tool off the shelf, and turn its crank, with *less* required understanding of the mathematics of how those tools actually work. But aside from the debate about the machine learning context, I hope readers will visit the gist link and actually read the code. I am repeatedly impressed by the combination of clarity and conciseness-- an optimization of a driving simulation, with cool video rendering of the results, all in less than 500 lines of code.
> I am repeatedly impressed by the combination of clarity and > conciseness Thanks, Eric! I had actually buried the code link at the bottom of the article because I didn't feel it wasn't quite up to my usual standards, and that was because I wasn't planning to discuss the code, just the concepts. I'm glad to hear it wasn't so unreadable as I feared!