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Lecture
Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
This lecture covers the basics of optimization, including definitions of metrics, vector norms, matrix norms, and convexity. It discusses continuity, differentiability, gradients, and convex functions. The lecture also explores logistic regression, strong convexity, convergence rates, and properties of strongly convex functions.