4. Fitting Logistic Regression using Maximum Likelihood Estimate (MLE).

This is what happens when you fit Logistic regression on binary classes using Maximum Likelihood Estimate (MLE).

Segregating two sets of 2D data points (red & green) using boundary or decision function. Regulate the decision function and you effectively regulate Sigmoid.

To catch more context behind this, please watch earlier videos in this series.