Linear Regression

The foundation of supervised learning. Fit a line through data using the least squares criterion and understand the geometry of prediction.

Learning Objectives

• →Derive the normal equation
• →Understand mean squared error loss
• →Implement prediction with weights
• →Evaluate with R² and RMSE

Practice