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Explore maximum likelihood estimation applied to regression problems in this 37-minute lecture from the University of Utah's Data Science program. Delve into Bayesian Learning concepts through a detailed worked example, understanding how maximum likelihood estimation connects to loss minimization in regression contexts. Build foundational knowledge in probabilistic machine learning approaches while examining practical applications of these statistical methods.
Syllabus
Machine Learning: Lecture 24a: Maximum Likelihood Estimation for Regression
Taught by
UofU Data Science