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Thought this was interesting. Across 160 teams of researchers, just about all failed to make good life outcome predictions on things like GPA, evictions, layoffs, and others. Data followed 4.5k families across 15 years, with 13k features (varied over time). Haven't looked at it directly yet, but will be turning the docs and data inside out... In the meantime, authors claim this as showing the limits of ML. Oh, and it's published in PNAS, so you know there's some big publication energy there.
https://www.pnas.org/content/117/15/8398
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When I did it (3 years ago) it was just hackerrank and it was really quick. The only thing I remember was needing to build a times series model in Python in 10 minutes.
Right?! I’d want to evaluate the RMSE and cumulative predictions of multiple models against multiple test sets and stage it incrementally. No way I could do that in 10 min. Not sure I like that method of interviewing.
Op - let us know how it goes