Sunday, January 17, 2016

Data science

Earlier, I wrote about "big daddy" data. Up until now, I have not been looking closely, rather my approach has several motivations.

So, before proceeding, I need to catch up on the world, in this sense. It looks like a bubble just like the early days of artificial intelligence. A boot camp of a few days, even weeks, is enough to become what is called a "data scientist?"

Aside: In all of the blogs, you will find reference to entrapping enmesh-ments which seem to be growing daily. But, we'll get back to that.

Some pointers to material:
Aside: One of the big splits relates to the computer as the focus. That is, we live in a world where real people touch real things in order for the coddled set to languish about. Yet, it is the computer types who seem to drive things, many times relegating those who touch things to some lower-level class of being. The uppers ride a magic carpet born on the sweat of millions. ... Jumping ahead, so, then, the computer as the basis for a whole lot of mathematical finagling is reality? Much to discuss there. 

Aside: Numerics, and its bridging over trouble waters, does not alleviate the problems that are inherent with the artificial. No one seems to be interested. Why?  

Remarks: Modified: 01/18/2016

01/18/2016 -- Hotten'd the links. Also, will be introducing crass commercialism into the discussion. This ought not be the driver of our internet or of our knowledge repositories.

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