Lecture Notes - Machine Learning

• class 1 math intro
• Class 2 Bayes
• Class 3a PAC learning
• Class 3b infinite hypothesis classes
• Class 4a linear and ridge regression
• Class 4b linear binary classification
• Class 5 multiclass and svm
• Class 6a nonlinear classification
• Class 6b dt and boosting
• Class 9a kmeans
• Class 9b EM
• Class 10a pca dim reduction
• Class 10b denoising ae
• Class 11 sequences
• Class 12a SSL
• Class 12b Diffusion