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Machine learning is not just glorified statistics

towardsdatascience.com

61–64 of 64 posts

Re: Machine learning is not just glorified statistics

#61
post #52

Earlier quoted context omitted.

> It certainly comes as a shock to all of the statisticians in the world who have indeed been working on these types problems for a long time now Yup on high dimensional data of dimension as fantastic as 12. I feel bad for them though but they have only themselves to blame -- got too comfortable within their small world and lost touch of what the next set of interesting problems are. Its only after getting kicked in…

Your response is so entirely off base I don't know where to begin. > Yup on high dimensional data of dimension as fantastic as 12 Who says that has been the limit of classical statistics. > If one computes stats on 600 data points with 10 dimensions and feels king of the hill, they can continue, but there is likelihood that some one else will be eating your lunch and you will be left behind. Again, why do you have th…

You basically went line by line to take too many words to say “you’re wrong”. That's how much content is left over after you filter out the insults.

Re: Machine learning is not just glorified statistics

#62
If you start your article with the assumption that ML is being a subject to memes because "it's not fashionable to like it" -- which also includes "liking" it, as if it's some kind of aesthetics art... Then your argument falls apart from the get go.

Perhaps the author should use ML itself to find out why people started mocking it!

Re: Machine learning is not just glorified statistics

#63

This is a terrible post, coming from someone who doesn't know statistics to claim something is not statistics.

his is a terrible post, coming from someone who doesn't know statistics to claim something is not statistics.

But the author went to Harvard, doncha know. Harvard.

Re: Machine learning is not just glorified statistics

#64

I would consider machine learning to be an application of statistics, in much the same way that mechanical engineering is an application of physics. The foundations of mechanical engineering are rooted in physical concepts, but mechanical engineers have formulas for all sorts of things, like calculating the fatigue life of gears, that you can't get from pure physics because they are empirically derived curve fits, ra…

>...you can't get from pure physics...

You could use natural laws, if you want to propagate a mess of uncertain parameters through a complicated forward problem. Interpolation within empirical data is wildly easier, but a masochist could do gear fatigue ab initio in silico.

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