# 11. Parameter Estimation - Stanford University

Maximum **Likelihood** Our ﬁrst algorithm for estimating parameters is called Maximum **Likelihood Estimation** (MLE). The central idea behind MLE is to select that parameters (q) that make the observed data the most likely. The data that we are going to use to estimate the parameters are going to be n independent and identically distributed (IID ...

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