Following on from the introduction of the univariate cost function and gradient descent in the previous post, we start to introduce multi-variate linear regression in this post and how this affects the hypothesis, cost function and gradient descent.

We start to cover important topics including vectorisation, multi-variate gradient descent, learning rate alpha for gradient descent tuning, feature scaling and normalisation.