sequential wrapper we have all of our layers all of these layers are composed of perceptrons or single neurons which we saw earlier the second line defines our optimizer which we saw in the previous slide this can be SGD it can also be any of those adaptive learning rates that we saw before now what we want to do is during our training loop it's very it's the same stories again as before nothing's changing here we forward pass all of our inputs through that model we get our predictions using those predictions we can evaluate them and compute our loss our loss tells us how