Lecture notes
A guide to the course notes. On this page I will post the course notes that will be used during each lecture. These will be slides, and will be posted before the lecture. After each lecture, the annotated slides will be posted too. One "Lecture" file may be used for more than one actual lecture. To eliminate confusion, the unannotated notes posted here will be titled Lecture I, Lecture II, etc, while the annotated notes after each lecture, will be titled L1a-jan6, L1p-jan6, L2a-jan8, etc. Additional materials not used in class will be posted here too.
- Lecture 0 Overview of Machine Learnng
- Lecture I Prediction: examples. The Nearest Neighbor (NN) predictor.
Annotated lecture slides
- L1a-jan6, L1p-jan6 What is ML?
- L2a-jan8, L2p-jan8 Predictors by type of output. Nearest neighbor predictor.
(--a = 11:30-12:50 section, --p = 4-5:20 section)
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