Below is our course schedule, which will almost certainly change as the course progresses. Details regarding evaluation due dates can be found below the table.
| Week | Date | Session | Title | Suggested Readings |
|---|---|---|---|---|
| 1 | 04-Jul | Lecture | Introduction | ISL (python) 1, 2.1-2.3 |
| 04-Jul | Tutorial | No Tutorial | ESL 1, 2.1-2.3, 2.6 | |
| 2 | 07-Jul | Lecture | Review of basic math and LEC1, Linear Model | ESL 3.1-3.2.2, ISL3.1-3.3 |
| 11-Jul | Tutorial | Validation Set | ISL 5.1 | |
| 11-Jul | Lecture | Cross-Validation, Regularized Linear Model | ISL 5.1, 6.2, ESL3.41-3.43 | |
| 3 | 14-Jul | Lecture | Gradient Descent, Classifcation, Logistic Regression | ESL 4.4, ISL 2.2, 4.1-4.3 |
| 18-Jul | Tutorial | Numerical Experiments for GD and Logistic Regression | ||
| 18-Jul | Lecture | Confusion Matrix, Convex Opt and Multiclass-Logistic Regression | ESL 4.4, ISL 2.2, 4.1-4.3 | |
| 4 | 21-Jul | Midterm | ||
| 25-Jul | Tutorial | GD with torch | ||
| 25-Jul | Lecture | LDA, QDA and Naive Bayes | ISL 4.4, ESL 4.1-4.32, MLAPP 4.1-4.2 | |
| 5 | 28-Jul | Lecture | Moving beyond linearity | ESL 61-6.2, ISL 10.1-10.2, 10.7 |
Assignments are to be submitted via Crowdmark.