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This lecture covers the Iteratively Reweighted Least Squares (IWLS) algorithm for obtaining Maximum Likelihood Estimates (MLEs) in regression models. The instructor explains the Newton-Raphson update step, the IWLS algorithm, and provides examples for normal linear, normal nonlinear, and Gumbel linear models. The lecture also discusses the likelihood ratio statistic and deviance in model fitting.