Logistic regression is a method for classifying data into discrete outcomes. For example, we might use logistic regression to classify an email as spam or not spam. In this module, we introduce the notion of classification, the cost function for logistic regression, and the application of logistic regression to multi-class classification. We are also covering regularization. Machine learning models need to generalize well to new examples that the model has not seen in practice. We’ll introduce regularization, which helps prevent models from overfitting the training data.