investigate how Regularization methods can affect on generalization of the models. methods like L2 Regularization, Dropout
Deep Learning models have so much flexibility and capacity that overfitting can be a serious problem, if the training dataset is not big enough. Sure it does well on the training set, but the learned network doesn't generalize to new examples that it has never seen!