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Confession: What makes me good at machine learning research makes my life miserable. And that is: I habitually stick with a problem until it's solved. The problem is that the problem can never truly be solved in machine learning. 1/
Engineering problems, in contrast, are generally finite. That's fun. The obsessive problem solving has a natural end: When the problem is solved. Two years of having an unsolved problem with this type of personality? That SUCKS. Now I know. 2/
I plan on writing more about this stuff later- about to wrap up research with a hard deadline. It's going to be a relief I think. Then what? Time to get a life again. 3/
This is something immature enterprise DS teams and organizations grapple with beyond a personal level too. The difference between meeting a functional spec (Eng) and asymptotically optimizing for a set of metrics (ML) is a fundamental one.
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