understand what is amiss for us learning let's look at supervised learning in supervised learning you have a joint distribution of data points and labels and use sample from the Joint Distribution in expectation over two samples from the Joint Distribution your goal is to maximize a lot of probability of the classifier love P of Y given X we all know how to do this as far as procedurally how it's done the basically sample image label or like sequence and particular label or any pair of x and y from your data set assuming they're all