Slides and notes for lectures will be posted here.
Topics may change based on student interest.
Lecture videos (Cornell only) available on Videonote one week after lecture.
Course topics
Introduction
Linear models
Generalization and overfitting
Nonlinear models
Regularization for messy features
Loss functions for messy labels
Logistic regression and Support Vector Machines (SVMs)
Multiclass and ordinal regression
Optimization: proximal subgradient
Unsupervised learning
Missing data and PCA
Sparse PCA, NNMF, kmeans
Optimization: AM and PALM
Learning from prototypes
Nearest neighbors
Smoothing
Graphs and networks
Advanced topics
Other resources
Review/overview
Julia
GitHub
