08:55
I'm very interesting in the outcome, as quite a few of my answers are relatively deep debug sessions into why a particular neural network is not functioning. It is not clear to me what long-term value these bring to the site, but AFAICS Data Science is one of the few places that questions like that can find a home at the moment.
On Stack Overflow, the debugging work requires too much NN theory. On stats.stackexchange the mood seems to switch between these being acceptable or off-topic depending on who is answering.
In my mind, the key differentiator for DS vs CV sites is handling practical questions on use of the tools. The key differentiator for DS vs SO is handling theory. But that makes this site a "site of the gaps" for these kind of problems, and means we end up handling some questions which are a bad fit in SO/CV and bring some baggage with them.
We probably need a more positive spin on what the site is actively for, as opposed to "we'll handle questions on topics that SO/CV cover, but that have the wrong angle for them"
To be clear, I am answering these kind of questions ("please help me fix my NN implementation") because it allows me to revise my own self-study, and they don't get asked in such volumes on SO or CV.
