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Apr 7, 2017 at 22:51 comment added Cliff AB I strongly agree with @gung; similar to other answers, I agree that this is more often the motivation for people who call themselves "ML researchers", its definitely not a defining line. Two counter examples: recommender systems are considered a ML research area, but the results are fed directly to a human. Kalman filters are very often used in navigation for auto-pilot, with no human in the loop, yet are typically considered to be a statistics methodology.
Mar 23, 2017 at 18:31 comment added Lawnmower Man I would say that's because ML as a field has spawned a variety of useful tools leveraged by statisticians, even if that's not what they want to call themselves, for marketing purposes. ;)
Mar 22, 2017 at 20:21 comment added gung - Reinstate Monica This is a reasonable point, but I think in practice ML models are often handed off to people to interpret & work with.
Mar 22, 2017 at 20:08 review First posts
Mar 22, 2017 at 20:21
Mar 22, 2017 at 20:07 history answered Lawnmower Man CC BY-SA 3.0