Statistical Methods in Machine Learning (36-708)

​Syllabus

Lecture notes:

• Intro & basics
• kNN & kernels
• Local polynomials
• Series estimation
• Density estimation
• Additive & partially linear models
• Random forests
• High-dimensional regression
• Cross-validation​
• Inference
• Aggregation
• Classification
• Clustering
• Semi-supervised & transfer learning
• Minimax theory