CS 311 Mathematical and Computational Foundations of Artifical Intelligence
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Foundations for analyzing and developing intelligent systems with essential concepts in linear algebra, probability, calculus, optimization, and statistical inference. Estimation and decision theory. Regression and regularization. Optimization. Dimensionality reduction. Matrix/tensor decomposition and efficient implementations. Monte Carlo sampling. Graphical models and efficient algorithms. Variational inference. Performance evaluation. Emphasis on theoretical understanding as well as computational applications in computer science.
Credit units: 3 ECTS Credit units: 5, Prerequisite:
(CS 202 or CS 211) and MATH 132 and MATH 225 and MATH 230.
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