Maximum Likelihood Estimation (MLE) with Examples @Eigensteve

Uploaded November 2025 | Updated September 2026, 1 week ago

This video introduces Maximum Likelihood Estimation (MLE), one of the most important methods in statistical parameter estimation. MLE is the basis of the Bayesian extension, maximum a posteriori (MAP) estimation.

This video was produced at the University of Washington, and we acknowledge funding support from the Boeing Company

%%% CHAPTERS %%%
00:00 Intro
01:05 Problem Statement of MLE
05:58 Deriving the Estimator
12:20 Example: MLE of a Poisson
19:00 Recap
21:45 Note on Prior Knowledge & Outro

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