data such that they can be useful for a lot of downstream tasks and this lecture is going to get at that and recently people have started calling this stuff supervised learning where the data creates its own supervision and so we are going to look at all the various classes of techniques that are allow us to do stuff supervised learning so so far we've seen density modeling where we've covered Auto regressive models flow models and we also talked about variational inference and we've also looked at implicit generative models