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I'm sort of confused as to how the nonlinearity of an activation function like the ReLu means that relatively complex mappings can all be approximated by a neural network? I guess I am sort of confused as to how neural networks are able to learn these functions in general.

Thanks

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marked as duplicate by Reinstate Monica, shimao, Michael R. Chernick, kjetil b halvorsen, mkt - Reinstate Monica Nov 29 '18 at 8:32

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