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I am trying to understand what neural nets have in common with multiple linear regressions. Is is correct that every node in every layer (not counting the input layer) is just a multiple regression with the variables being the nodes in the preceding layer? I've included a picture to show what I mean. How is this understanding wrong/right?

enter image description here

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marked as duplicate by Franck Dernoncourt, mdewey, kjetil b halvorsen, Community Mar 2 '17 at 19:37

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