On the Terms We Use

Good discussion on the terms we use.  With some good graphics included later in the article, click through.

Machine Learning – Can We Please Just Agree What This Means

Posted by William Vorhies  in DSC

Summary:  As a profession we do a pretty poor job of agreeing on good naming conventions for really important parts of our professional lives.  “Machine Learning” is just the most recent case in point.  It’s had a perfectly good definition for a very long time, but now the deep learning folks are trying to hijack the term.  Come on folks.  Let’s make up our minds.

As a profession we do a pretty poor job of agreeing on good naming conventions for really important parts of our professional lives.  How about ‘Big Data’?  Terrible.  It’s not about just size although if you asked most non-DS practitioners that’s what they’d say.  Or how about ‘Data Scientist’.  Nope.  Can’t really agree on that one either.

Now we come to ‘Machine Learning’.  If you asked 95 out of 100 data scientists, specifically those who are not doing deep learning they would unanimously agree that this definition hasn’t changed over at least the last 15 years:

The application of any computer-enabled algorithm that can be applied against a data set to find a pattern in the data.  This encompasses basically all types of data science algorithms, supervised, unsupervised, segmentation, classification, and regression including deep learning.... "