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Lecture
Generalized Linear Models
Description
This lecture covers the concept of Generalized Linear Models, including the assumptions, statistical properties, and practical applications. It delves into various topics such as high-dimensional statistics, Bayesian methods, compressed sensing, and perception. The instructor discusses the challenges of working with noisy data and the importance of understanding the linearized models in different contexts.
Official source
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