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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
today I choose violence

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Groups are pretty static. Sets are more dynamic and are great for showing elements in the set vs others. One example use case for sets is displaying top 10 vs other easily. You can also leverage set actions with sets.
Sets don’t have operations
/mathjokes
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Why don’t you just use them and find out? Kind of a silly question.
Also, having a consultant distill this down to a succinct layperson answer is way more effective than going the Google route imo
Sets vs Groups.
Sets can help you convine different sources, while group can only be one.
Coach
I don’t know
Coach
Lol what
Do you mean a dataset vs groups of values within a dimension or measure?
There is another website that might be helpful. I don’t recall the URL but it is by a company called Google.