the exercise this exercise is jumping back a little bit to earlier how I described that there's a different cost function that you can use for maximum likelihood and generative adversarial networks and I think this is a really good closing exercise because it really drives home the point that the key mathematical tool generative a versatile networks give you is the ability to estimate a ratio and to see how the estimate ratio estimation works you are going to derive the maximum likelihood learning rule in particular