call W 1 and W 2 so its corresponds to the first layer and the second layer if we look at a single unit inside of that hidden layer take for example Z 2 I'm showing here that's just a single perceptron like we talked about before it's taking a weighted sum of all of those inputs that feed into it and it applies the non-linearity and feeds it on to the next layer same story as before this picture actually looks a little bit messy so what I want to do is actually clean things up a little bit for you and I'm gonna replace all of those lines with just this symbolic representation