Supplementary references are to the following textbook:
Trevor Hastie, Robert Tibshirani, and Jerome Friedman, The Elements of Statistical Learning (2nd edition)
It is available online through Roger and is referred to below as HTF.
| Jan 8 | Nearest neighbor classification [HTF 2.3, 7.10, 13.3]
Evening discussion: Python / NumPy tips |
| Jan 10 | A host of prediction problems [HTF 2.1, 2.2]
Probability review |
| Jan 15 | Probability review (cont'd)
The generative approach to classification Homework 1 due (6pm) Evening discussion: Probability |
| Jan 17 | The generative approach to classification
Quiz 1 (based on HW1) |
| Jan 22 | Linear algebra primer
Homework 2 due Evening discussion: Linear algebra |
| Jan 24 | Multivariate generative modeling |
| Jan 29 | Multivariate generative modeling (cont'd)
Linear regression [HTF 2.3.1, 3.2, 3.4] Homework 3 due Evening discussion: HW3 |
| Jan 31 | Linear regression (cont'd)
Quiz 2 (based on HW2 and HW3) |
| Feb 5 | Linear regression (cont'd)
Logistic regression [HTF 4.4] Homework 4 due Evening discussion: Multivariate differentiation |
| Feb 7 | Unconstrained optimization |
| Feb 12 | Convexity
Homework 5 due Evening discussion: Optimization |
| Feb 14 | Linear classification [HTF 4.5, 12.1, 12.2]
Quiz 3 (based on HW4 and HW5) |
| Feb 19 | Linear classification (cont'd)
Homework 6 due Evening discussion: Perceptron and SVM |
| Feb 21 | Multiclass linear prediction
Decision trees [HTF 9.2] |
| Feb 26 | Boosting
Random forests Homework 7 due Evening discussion: Review for Thursday's quiz |
| Feb 28 | Clustering
Quiz 4 (based on HW6 and HW7) |
| Mar 5 | Clustering (cont'd)
Evening discussion: Eigenvalues and eigenvectors |
| Mar 7 | Informative projections |
| Mar 12 | Informative projections (cont'd)
Neural nets Homework 8 due Evening discussion: Review for Thursday's quiz |
| Mar 14 | Quiz 5 |