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I've seen the term "machine learning" used without criticism to refer to such a wide range of things that it seems pretty much synonymous now with multivariate

I've seen the term "machine learning" used without criticism to refer to such a wide range of things that it seems pretty much synonymous now with multivariate discrimination and classification. At one time I would have said "machine learning" meant "deep learning models" but then it seemed to mean "computational multivariate discrimination and classification" and now the "computational" doesn't even apply. I personally believe "machine learning" is a term that could be removed from use and nothing would suffer (and clarity might even be improved). I feel somewhat similarly about "data science" although at least that captures some intersection of database engineering and computational statistics that is useful when discussing very large data problems.

mistrial9 4y ago
> seen the term "machine learning" used without criticism yes > would have said "machine learning" meant "deep learning models" no not at all.. DeepLearning has gotten serious technical press since about 2015 when certain competitions yielded better-than-average-human performance. DL is also closely coupled to the business model of massive cloud providers who handle streams of digital media. Yet ML stats continue to reliably predict eighty-percent plus well, on lots of kinds of problems. > it seemed to mean "computational multivariate discrimination and classification" no, classification has always been on of two main uses for ML, the other being regression-style prediction of real values. > believe "machine learning" is a term that could be removed from use no, stats are useful and continue to be useful. It is AI that is the really wonky term, to my ear. Please consider that there is a lot of difference between academic statistical methods, and technical press product hype. You may be suggesting a change in media coverage jargon, but you know, good luck with that..
mr_toad 4y ago
> At one time I would have said "machine learning" meant "deep learning models" The early ML models used SVMs, Logistic Regression and Naive Bayes. Not deep at all. What made them ML models was the size of the feature sets data, and the use of automated feature selection.

mistrial9 4y ago

> seen the term "machine learning" used without criticism yes > would have said "machine learning" meant "deep learning models" no not at all.. DeepLearning has gotten serious technical press since about 2015 when certain competitions yielded better-than-average-human performance. DL is also closely coupled to the business model of massive cloud providers who handle streams of digital media. Yet ML stats continue to reliably predict eighty-percent plus well, on lots of kinds of problems. > it seemed to mean "computational multivariate discrimination and classification" no, classification has always been on of two main uses for ML, the other being regression-style prediction of real values. > believe "machine learning" is a term that could be removed from use no, stats are useful and continue to be useful. It is AI that is the really wonky term, to my ear. Please consider that there is a lot of difference between academic statistical methods, and technical press product hype. You may be suggesting a change in media coverage jargon, but you know, good luck with that..

mr_toad 4y ago

> At one time I would have said "machine learning" meant "deep learning models" The early ML models used SVMs, Logistic Regression and Naive Bayes. Not deep at all. What made them ML models was the size of the feature sets data, and the use of automated feature selection.