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> it's kinda ridiculous to try compressing a college degree's worth of knowledge into a bunch of sleek online tutorials.

Honest question, why?

We used to give degrees (albeit hundreds of years ago) for material that now is covered, at a high level, in a single course (e.g. physical sciences). The amount of material to cover, and to master, increases dramatically over time. It makes sense to compress the knowledge to be delivered to a compendium so as to simply keep up with progress.




Not OP but I suspect they will say something about the math behind it. It's very true you can get quite adept at plug-and-play machine learning models (and indeed be quite successful) but the theoretical statistics, linear algebra and overall mathematical maturity take a long time to develop in my opinion.


Yep, the great thing about tensorflow are the canned algorithms. You can focus on your data-sets and problem rather than deep theory.




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