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They need both. Having a domain expert in the domain you are modelling will save you a lot time and lets you avoid a lot of dumb mistakes.
by dagw 8y ago
They need both. Having a domain expert in the domain you are modelling will save you a lot time and lets you avoid a lot of dumb mistakes.
- 4thaccount 8y agoYea. In my industry you could hire a team of generalists and I wouldn't expect any of their conclusions to be valid. Now if a domain expert can get them a valid dataset...then they can do some statistics and analysis and maybe uncover something I wouldn't notice.
- deleted 8y ago[deleted]
- 0815test 8y agoAlso, you need domain expertise to do good feature engineering and to develop good tailored architectures. These are quite critical to obtaining SOTA results, so far as I can tell. People like to pretend that deep learning and "AI" have made feature/model engineering unnecessary, and it's just not true.
- hikkigaya 8y agoNot really, you don't need to be an expert in go to beat the best go player.
- nerdponx 8y agoI'd be very surprised if the AlphaGo team didn't at least consult with a few Go players...
- bloomer 8y agoExcept go (and all other well defined games) are the most trivial of domains. For real business problems, the difficulty is most often trying to determine what the problem is and how it relates to the rest of the world.
- currymj 8y agothere was a strong model of the world in AlphaGo, which allowed it to accurately simulate games that followed the rules. that is quite a lot of domain expertise, much more than in most ML systems.
- natalyarostova 8y agoAnother way of saying this, is you don't really need the same level of domain expertise if the problem space is entirely defined by a small set of clearly articulated rules.
- deleted 8y ago[deleted]