implicit density models like jion's and energy based models and both these classes of techniques allow you to learn generative models which is you are going to be able to generate images and be able to report lac courte scores and so on but other than that we mainly looked at applications of generative models to various modalities of data we haven't actually seen how to use unsupervised learning to learn features so that's the motivation for today's lecture how do we learn rich and useful features from raw unlabeled Ino such that it can be useful