Part 1: Linear Regression — What the Model Actually Does Linear regression is one of the simplest predictive models in machine learning. Its job is straightforward: learn the relationship between a set of input features and a continuous target by fitting the best possible line through the data. If you have many features, that "line" becomes a hyperplane, but the underlying idea stays the same. For multiple features, the model can be written as: ŷ = β₀ + β₁x₁ + β₂x₂ + ... + βₙxₙ Wh...