# Python: Maximum Likelihood Estimate

In this post I want to talk about regression and the maximum likelihood estimate. Instead of going the usual way of deriving the least square (LS) estimate which conincides with the maximum likelihood (ML) under the assumption of normally distributed noise, I want to take a different route. Here, instead of using the analytical LS solution, I want to show you, how we can numerically … Continue reading Python: Maximum Likelihood Estimate