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MATH 462 Honours Mathematics for Machine Learning (3 credits)

Offered by: Mathematics and Statistics (Faculty of Science)


Mathematics & Statistics (Sci) : Foundations of optimization and convex analysis, stochastic gradient descent. Divergences, loss functions, empirical loss minimization and parameter estimation. Reproducing kernel Hilbert spaces. Multiple linear regression in the context of machine learning. Classification with support vector machines. Dimensionality reduction, Johnson-Lindenstrauss Lemma. Concentration of measure and learning bounds.

Terms: Fall 2021

Instructors: Oberman, Adam (Fall)

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