I was an instructor for Machine Learning Summer School @ Columbia for a session on mechanistic interpretability in June 2026. Below are my slides and other materials.

• html slides (preferred)

• pdf slides

• interactive demos:

  • Universal function approximation theorem
  • Simple 2D classifier, LIME explainability
  • In-browser transformer demo, logit lens and tuned lens
  • Toy model of superposition