introduction to machine learning and deep learning plt xlabel( "$\lambda$"plt ylabel("rmse"plt legend(["train""test"]loc plt show(we can compute the value of using the closed form (xtx li)- xty we illustrate keeping the degree fixed at value of and varying the value of in listing - the training rmse (seen dataand test rmse (unseen datais plotted in figure - figure - regularization we see that the test rmse reduces gradually to the minimum and then gradually increases as the model capacity increasesresulting in overfitting ummary this covered brief history of deep learning and introduced the foundations of machine learningincluding examples of supervised learning (classification and regressionthe key points for this