and try to improve our classifiers it just works with the label data and how you do it is totally up to you and that basically decides what kind of summarized algorithm you're gonna come up with to use and we're gonna look at in this lecture we're going to look at how these algorithms can be designed what are the mathematical or intuitive aspects of these algorithms and how you compare each other and how they can scale the larger data sets like image that and beyond so as to why we even interested in this problem semi-supervised learning is