This schedule is tentative and may change.
| Date | Topic | Materials |
|---|---|---|
| June 5 | Course Introcuction, Supervised Learning | |
| June 10 | Supervised Learning, Logistic Regression, HW1 Out | |
| June 12 | Review of Probability Theory, Linear Discriminant Analysis | |
| June 17 | Naive Bayes, Kernels, HW2 Out | |
| June 19 | Juneteenth Holiday |
|
| June 24 | Support Vector Machine | |
| June 26 | Neural Networks | |
| July 1 | Backpropagation, Bias-Variance Tradeoff, HW3 Out | |
| July 3 | Decision Trees | |
| July 8 | Deep Learning | |
| July 10 | Convolutional Neural Networks | |
| July 15 | Boosting | |
| July 17 | PyTorch Tutorial, HW4 Out |
|
| July 22 | Optimization for Deep learning | |
| July 24 | Markov Decision Processes | |
| July 29 | Reinforcement Learning | |
| July 31 | Unsupervised Learning | |
| August 5 | Attention Mechanism, Transformers | |
| August 7 | Project Presentations |
|