I'm wondering where I should ask question related to my field of interest (e.g.: qlearning, etc).

I'm aware code focused question isn't the right place in datascience, so I'm wondering where would be the right place on stackexchange. I guess SO could work but the problem I noticed is that there less eagerness in answering datascience related question there when code is involved, even in the likely event that training/fitting is not needed to reproduce problems.


1 Answer 1


To me, it depends on how much the problem is actually code/debugging vs. statistical/etc. If it's primarily code, then ask on SO even if it requires some minor data science or specialized background to fully understand the context. If the main question is rather about some data science decision or understanding (even if it involves code), or if it's about code but really requires more advanced data science knowledge, then ask here.

All that is advice for askers, but I wouldn't vote to close anything reasonably close to on-topic on either site.

  • $\begingroup$ got you :) for context I implemented a couple of qlearning paper and algorithm but I wanted to get second opinion on why it has specific behavior or if I implemented it wrong somehow (in python). $\endgroup$ Dec 26, 2023 at 7:11
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    $\begingroup$ @NordineLotfi and that's a troublesome edge case: when you don't know whether the underlying issue is a misunderstanding of the algorithm or a code error. I'd lean toward asking here in such a case. You might be able to tailor two questions in such a case: on SO, "is there a bug?" and here "did I misunderstand what should happen?", prominently linking them to each other. $\endgroup$
    – Ben Reiniger Mod
    Dec 26, 2023 at 16:05
  • $\begingroup$ That's a very good way to approach this! Thank you, will do $\endgroup$ Dec 26, 2023 at 16:20

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