Discussion sections are a chance to go over the material in more depth, ask questions, and work on problems together. They will be led by TAs for the course. Attendance is optional but highly encouraged.
List of section locations/TAs (all discussion sections meet weekly on Fridays):| Date | Content | Resources |
|---|---|---|
| 9/26 | Python, Probability Fundamentals, Linear Algebra |
Section notes,
Solutions,
Python intro (source),
html,
viewable link,
Python slide deck
Varun's notes |
| 10/3 | Data Normalization and Linear Algebra | Section notes, Solutions, Varun's notes |
| 10/10 | Vector Calculus, Bias and Estimation | Section notes, Solutions, Varun's notes |
| 10/17 | Train-Test Splitting, Generalized Least Squares Regression, MAP as Regularization | Section notes, Solutions, Varun's notes |
| 10/24 | Midterm Prep (+ Cross Validation, Convexity) | Section notes, Solutions, K-fold demo notebook, Lasso and CV demo notebook, Varun's notes, Autumn 2024 Midterm |
| 10/31 | Intro to PyTorch, SGD | Section notes, Solutions, Varun's notes, PyTorch Introduction (file), Colab viewable link |
| 11/7 | Kernels, PyTorch | |
| 11/14 | Neural Networks | |
| 11/21 | PCA, SVD, Convolutional Neural Networks (including HW4 background) | |
| 12/5 | Final Review, Next Steps |