introduction to machine learning and deep learning note that instead of the prediction being binary class label + like in binary classificationwe have real valued prediction we measure performance over this task as the root-mean-square error (rmseover unseen data yi xi du  note that the rmse is simply taking the difference between the predicted and actual valuesquaring it so as to account for both positive and negative differencestaking the mean so as to aggregate over all the unseen dataandfinallytaking the square root so as to counterbalance the square operation real-world problem that corresponds to the abstract task of regression is to predict the credit score for an individual based on their financial historywhich can be used by credit card company to extend the line of credit generalization let' now cover what is the single most important intuition in machine leaningwhich is that we want to develop/generate models that have good performance over unseen data in order to do thatfirst will we introduce toy data set for regression task laterwe will develop three different models using the same dataset with varying levels of complexity and study how the results differ to understand intuitively the concept of generalization