4 ms·
I find these definitions funny…. how statisticians vs computer scientists define machine learning differently. You get two different perspectives. Everyone wa
by thrown321 4y ago
I find these definitions funny…. how statisticians vs computer scientists define machine learning differently. You get two different perspectives. Everyone wants to claim AI for themselves. I think the statisticians are pissed off that DNNs works so well.
Anyway least we forget: Neural networks came from cybernetics!
- qqqwwweeerrr 4y agoI never claimed that everyone wants to claim AI for themselves. Artificial intelligence is ofcourse a scientific field on it's own right, even before machine learning was a thing. I'm just saying that AI scientists have used concepts from statistics to create an approach to AI called machine learning. I'm not saying that ML is a subset of statistics, mind you, but the statistical underpinnings of it definitely are. ML is not _just_ statistics too. Moreover, why would statisticians be pissed about the efficacy of a model? Firstly, many problems/questions that I work on are not concerned with prediction. Secondly, even if I did, I would love to use DNNs. It's just that I never have a use for it considering I'm only looking at tabular data. Why bother with DNNs when, say, a random forest will do?