Linear Models: Classification

This lecture covers linear models for classification, including binary classification as regression, logistic regression, decision boundaries, and support vector machines. It also discusses multi-class classification, one-hot encodings, and the application of linear models to real datasets. The instructor explains the drawbacks of least-square classification, the gradient descent algorithm, and the comparison of linear classifiers using practical examples.