Linear Regression, Gradient Descent, Machine Learning, Data Science, Getting Started.
slope and y-intercept. You compute the sum of squared errors again for your new line. You continue adjusting until you reach a local minimum, where the sum of squared errors is the smallest and additional tweaks does not produce better result. The way you adjust your slope and intercept will be