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), colabpractice, solutions, notes (by Soumita)
02/07 Multiclass classification; neural networksslides, handouts (1-page, 4-page), demoBackprop explainer (by Dongze)
02/14 Convolutional neural nets; kernel methodsslides, handouts (1-page, 4-page), demopractice, solutions, HW1_review (by Robby)
02/21 Lagrangian duality; SVM slides, handouts (1-page, 4-page), colab quiz1_2021, quiz1_2021_sol (by Xiao)
02/28 Decision trees; boosting slides, handouts (1-page, 4-page)quiz1_2024, quiz1_2024_sol (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 Robby)
04/04 (Hidden) Markov models(by Soumita)
04/11 Recurrent neural nets; attention; transformers;
large language models
(by Robby)
04/18 Multi-armed bandits; preference learning; learning in games(by Robby)
04/25 (Deep) reinforcement learning(by Dongze)
05/02 Quiz 2