wrong our network was on that iteration it also tells us how we can compute the gradients and how we can change all of the weights in the network to improve in the future and then the final line there takes those gradients and actually allows our optimizer to update the weights and the trainable variables such that on the next iteration they do a little bit better and over time if you keep looping this will converge and hopefully you should fit your data no now I want to continue to talk about some tips for training these networks in