What you say is true but in terms of hiring and screening candidates it really depends.

One important aspect of all skills is to know the limitations and boundaries of said skill. It’s probably fine if somebody implemented ML on a trivial problem to learn and practice, but if they didn’t realize there could be better solutions in the first place and that ML isn’t a solution to everything, then it’s a big red flag for me.

Also, finding a good problem for a solution is also a handy skill, if one can’t figure out how to apply their skills to a real problem, then that does give slightly negative impressions.