Sebastian Raschka

Just throwing in some references ... a general one regarding easily picking up spurious correlations (or rather systematic noise) is - Jo, J., & Bengio, Y. (2017). Measuring the tendency...

I agree, this is a fairly important one! On the flip-side, this is not unique to Deep Learning and applied basically to machine learning in general. Nonetheless, I feel like...

Regarding performance metrics etc. just want to throw in this reference: - Korotcov A, Tkachenko V, Russo DP, Ekins S: Comparison of Deep Learning With Multiple Machine Learning Methods and...

Totally agree with that. Also support that using logistic regression (and maybe random forest as a reference) would be sufficient as a baseline if we don't want to turn every...

> The problem is that validation is common terminology for what comes after testing for many people in biomedical research. You can argue that using validation for what comes before...

I agree with you @evancofer in a traditional machine learning setting, but imho @jmschrei is right if we narrow it down to DL (here, I mean CNNs, RNNs etc, not...

Thanks for the comment. I was just double checking and it looks correct to me: 

Thanks a lot, this looks cool. While some notebooks execute fine there are a couple of issues. I.e., the first cell (watermark) does cause an error because watermark is not...

Thanks! A little formatting related issue:  Does this one button not render properly because the line is too long, or is there...

Nice, thanks, seems to work now! > the "learning" from the title and just call it "Best practices for...", I would maybe leave the "Learning" because that corresponds to the...