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