[davidkell]

IMO no one has done more to make deep learning accessible than Jeremy + fast.ai team. Thanks for the amazing work!

My question is about the coding style - @jph00 I’ve read your fast.ai style guide and worked with APLs like q/KDB (written by Arthur Whitney who you cite).

My experience is that brevity is great, until you need to collaborate or have individuals working on small parts. That was my experience as well trying to write an extension to the fast.ai code (where I had to read large amounts of source to understand how to implement a small change).

Given that a key motivator for literate programming is collaboration/communication, how do you think about this?

[evanrich]

I fully agree here. I am working through Deep Learning for Coders now. I have created several errors as I am implementing chapters, but the coding style of fastai makes in impenetrable to debug. It’s an incredible book and a great library when its working as expected, but the number of times i have run into some variant of `method takes N parameters but M were given` is pretty frustrating. Looking through the stack, these are not patterns that would have been accepted in a code review from me for the same reason you mentioned. Making small changes and debugging are both hampered by the style.