We can compress our cost function's two conditional cases into one case:
We can fully write out our entire cost function as follows:
A vectorized implementation is:
Gradient Descent
Remember that the general form of gradient descent is:
We can work out the derivative part using calculus to get:
Notice that this algorithm is identical to the one we used in linear regression. We still have to simultaneously update all values in theta.
A vectorized implementation is:
