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Machine Learning (Spring 2025)
Schedule is subject to small adjustments.
Slides will be posted before each lecture (and might be updated slightly soon after the lecture).
Lecture/discussion recordings are available on DEN.
| Date | Topics | Slides | Discussion Session |
| 01/17 | Overview; nearest neighbor classification; core ML concepts | slides, handouts (1-page, 4-page) | math exercises, solutions, notes (by Dongze) |
| 01/24 | Linear regression; regression with nonlinear basis;
regularized regression | slides, handouts (1-page, 4-page) | practice solutions notes (by Xiao) |
| 01/31 | Linear classifiers; Perceptron; logistic regression;
general optimization algorithms | slides, handouts (1-page, 4-page), colab | practice (by Soumita) |
| 02/07 | Multiclass classification; neural networks | | (by Dongze) |
| 02/14 | Convolutional neural nets; kernel methods | | (by Robby) |
| 02/21 | Lagrangian duality; SVM | | (by Xiao) |
| 02/28 | Decision trees; boosting | | (by Xiao) |
| 03/07 | Quiz 1 | | |
| 03/14 | Clustering; k-means; Gaussian mixture models; EM | | (by Soumita) |
| 03/21 | Spring Recess | | |
| 03/28 | Density estimation; naive Bayes;
dimensionality reduction and visualization; PCA | | (by Dongze) |
| 04/04 | (Hidden) Markov models | | (by Soumita) |
| 04/11 | Recurrent neural nets; attention; transformers;
large language models | | (by Robby) |
| 04/18 | Multi-armed bandits; reinforcement learning | | (by Robby) |
| 04/25 | Deep reinforcement learning | | (by Robby) |
| 05/02 | Quiz 2 | |
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