In this video, you will understand how a logistic regression arrives at the decision boundary to separate the given data points into different classes.
you will also get to understand that decision boundary is characteristic of the learnt parameters not that of the data set.
There can be any kind (different shape) of decision boundaries. In this video you will get an idea as how a linear decision boundary is established and it's dependency on the form of hypothesis.
Log odds and maximum likelihood: https://youtu.be/_1kIlACzrew
Gradient Descent algorithm: https://youtu.be/sWl5dBflLbw
