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| Week: date | Topic(s) | Course | Readings | Additional information | |
|---|---|---|---|---|---|
| 1: 8/26 | Intro to Applied Analytics -- ML pipeline | Slides | None | ||
| 1: 8/28 | Review of R; manipulating data; using tidyverse | R review | None | Bring your laptop to class with R and Rstudio installed | |
| 2: 9/2 Monday: no class, 9/4 | Decision trees and logistic regression | Slides | ISL 4.3, 4.6, 8, 2.2 | HW 0 check-in | |
| 3: 9/9, 9/11 | Logistic regression, evaluating predictions | Slides | ISL 4.3, 4.6, 8, 2.2 | HW 1 to be released | |
| 4: 9/16, 9/18 | Evaluating predictions | Slides | Written HW 1 to be released | ||
| 5: 9/23, 9/25 | Discussion of readings; missing data | 9/25 10:30am: HW 1 due | reading 1 (abstract only); reading 2 | ||
| 6: 9/30, 10/2 | Bayesian networks | 10/2 10:30am: Written HW 1 due | Murphy 8.6, ESL 9.6, Murphy 10, 11 | ||
| 7: 10/7, 10/9 | Ensembles | Slides, partner requests due 10/9 | ISL 8.2, 6.2 | HW 2 to be released | |
| 8: 10/14, 10/16 | GLM variants, neural networks 1 | Slides | 7.3, 7.7; Murphy 28; Deep Learning Cheat Sheet; Deep Learning 2017 (slides) | ||
| 9: 10/21, 10/23 | Neural networks 2 | 10/23 10:30am: HW 2 due | |||
| 10: 10/28, 10/30 | Neural networks 3 | Proposals due 10/30 | Supplementary reading: Understanding LSTMs, From GAN to WGAN | ||
| 11: 11/4, 11/6 | Language modeling | Slides | Latent Dirichlet allocation; word2vec | ||
| 12: 11/11, 11/13 | Survival analysis | 11/13 10:30am: HW 3 due | CASI 9 | ||
| 13: 11/18, 11/20 | Final project workday (11/18); survival analysis 2 | Slides | Written HW 2 to be released | ||
| 14: 11/25, 11/27 Wednesday no class: Thanksgiving break | Support vector machines | 11/27 10:30am: Written HW 2 due | ISL 9 | ||
| 15: 12/2, 12/4 | Support vector machines; technical debt | 12/4: final project due: extended to 12/6 end of day | On technical debt; Rules of ML |
Note: bold indicates graded material