Machine Learning (Fall 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 |
08/29 | Overview; nearest neighbor classification; core ML concepts | | |
09/05 | Linear regression; regression with nonlinear basis; regularized regression | | |
09/12 | Linear classifiers; Perceptron; logistic regression; general optimization algorithms | | |
09/19 | Multiclass classification; kernel methods | | |
09/26 | Neural networks; convolutional neural nets | | |
10/03 | SVM; decision trees; boosting | | |
10/10 | Fall Recess | | |
10/17 | Exam 1 | | |
10/24 | Clustering; K-means; Gaussian mixture models; EM | | |
10/31 | Dimensionality reduction and visualization; PCA; Markov models | | |
11/07 | Recurrent neural nets; attention; transformers; large language models | | |
11/14 | Multi-armed bandits; preference learning; learning in games | | |
11/21 | (Deep) reinforcement learning | | |
11/28 | Thanksgiving | | |
12/05 | Exam 2 | |
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