Cost Function, Non Convex Optimization, Logistic Regression, Log Loss Function.
examples is represented by feature vector that’s N plus 1 dimensional. And as usual we have X 0 equals 1. Our first feature, or our 0 feature is always equal to 1, and because this is a classification problem, our training set has the property that every label Y, is either 0 or 1. This is a