What is the right place to ask question about how to design code for data science using TensorFlow?

Question

I was wondering if this site was a good place to ask about design patterns or ways to design code that works well for data science specifically. I had in mind to post a specific question on good coding practice using TensorFlow. What stack exchange site is a good place to post my question? Is this one good?

In particular, I wanted to know what good practices for how to design TensorFlow code when using GPUs on a single machine (not distributed machines) but potentially multiple GPUs. For example, what are the differences I should take into consideration when scaling up to use GPUs? Should I for example, stop evaluating how my model is doing every iteration using the whole data set? Are there other considerations I might not even be aware when using GPUs? I've had some memory complaints from TensorFlow when I use GPUs, so maybe I might not be allocating enough memory? How does the memory and the GPU interact with each other?

Answer 1

The more it's about debugging, code, hardware, and tuning, I'd say StackOverflow is more appropriate. The more it's about the problem design, modeling process, interpretation of outputs, the more it's appropriate here. For questions that are entirely about the theory, Cross Validated is probably best. There is overlap and there are many questions that are viable on more than one SE.