Sebastian Raschka

I think #88 is a bit too ambitious and given that this is a broad audience, it will only be useful to a very very small subset because demos are...

I don't see it covered in Tip 1. In Tip 3, we have > Similar to Tip 4, try to start with a relatively smaller network and increase the size...

Yeah. Unfortunately, there's no real guideline (similar to classic machine learning where there is no hard recommendation for which feature engineering approach should be used), we could maybe really give...

Good point. NVIDIA's GPU grant program is definitely nice and worth mentioning for smaller projects. Regarding the cloud credit, that's another thing to consider. I think AWS's program is mainly...

This is nice! I think it would be good to add a few sentences about this in ./content/10.blackbox.md I.e., saying that DL also offers new opportunities for interpreting results.

I think "Tip 2: Use traditional methods to establish performance baselines" seems to be the best place for that imho. Do you suggest a different tip?

Oh I see! Never really used this "project assignment" features and thought this was a "manually written" message :)

I think this could also fall under the category "Don't forget your ML fundamentals/Rules that apply to ML also apply to DL" (#37)

I think it would be good to have your suggestion as s a separate rule, but it is also somewhat connected #42, the fact that we need to usually have...

An additional reference regarding comparisons of neural networks with traditional methods in bio is - Koutsoukas, Alexios, et al. "Deep-learning: investigating deep neural networks hyper-parameters and comparison of performance to...