which ideally we end up with a model in the middle that is not too complex to memorize all of our training data but also one that will continue to generalize when it sees new data so to address this problem of regularization in neural network specifically let's talk about a technique of regularization which is another way that we can deal with this and what this is doing is it's trying to discourage complex information from being learned so we want to eliminate the model from actually learning to memorize the training data