Logistic Regression, Machine Learning, Hypothesis, Sigmoid Function.
also have that H of X must be between 0 and 1. Finally, given this hypothesis representation, what we need to do, as before, is fit the parameters theta to our data. So given a training set, we need to pick a value for the parameters theta and this hypothesis will then let us make predictions.