Basics Linear Regression Introduction Simple regression Making predictions Cost function Gradient descent Training Model evaluation Summary Multivariable regression Growing complexity Normalization Making predictions Initialize weights Cost function Gradient descent Simplifying with matrices Bias term Model evaluation Gradient Descent Introduction Learning rate Cost function Step-by-step Logistic