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EECS 127/227A: Convex Optimization for Machine Learning

This course offers the theories behind optimization models and their applications, ranging from machine learning and statistics to decision-making and control, with emphasis on numerically tractable problems, such as linear, quadratic, conic, or constrained least-squares optimization. Course link