Cost Function, Non Convex Optimization, Logistic Regression, Log Loss Function.
this is, that is 1/2 times the square difference between what are predicted and the actual value that we observe for Y. Now, this cost function worked fine for linear regression, but here we’re interested in logistic regression. If we could minimize this cost function that is plugged into J here.