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These are explanations that make sense to people who already know how deep learning works but don't really explain much to beginners beyond giving them a grossly oversimplified misrepresentation of what is being discussed (while not actually explaining anything).

My advice to folks is, if you actually want to know how this stuff works at some basic level, put in some time learning how basic linear and logistic regression work, including how to train it using back propagation. From there you'll have a solid foundation that gives enough context to understand most deep learning concepts at a high level.



It was intended as a demystification, not a total explanation. There are millions of places explaining with technical details.




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