Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
Lecture
Maximum Likelihood Estimation
Description
This lecture covers the concept of maximum likelihood estimation, which is a general method for estimating parameters in statistical models. It includes discussions on Bernoulli distribution, log-likelihood, Fisher information, bias, variance, and mean squared error. The instructor explains the importance of maximizing the log-likelihood function, calculating observed and expected information, and assessing the consistency of estimators.
Official source
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.