[bearzoo]

For work a month ago I implemented stochastic gradient descent in some arbitrary directed graph of operations (I applied a skill I learned from neural networks in a system that had nothing to do with neural networks) which required me to know how to take derivatives of a loss function with respect to parameters. I did all of the math on paper, and then coded it and it worked (to be frank this surprised me). It often may be hard to see the immediate gains from understanding things in a more technical, low level fashion - but I think in the long run they give you a great deal of power.