You want to predict something. A number. How much a house will sell for. How many units you'll sell next month. What temperature it'll be tomorrow. That's a regression problem. And linear regression is the first tool you reach for. It's the simplest ML model that actually does something useful. Every more complex model builds on the ideas here. You can't skip this one. What You'll Learn Here What linear regression actually does The equation y = mx + b and what each part means in ML What a cost function is and why we need one How least squares fitting works Building linear regression from scratch and with scikit-learn How to evaluate regression models (not accuracy, different metrics) Multiple features and what changes The Simplest Idea in ML You have two things that seem related. Hours studied and exam score. House size and house price. Temperature and ice cream sales. Plot them on a graph. You get a scatter of dots. Linear regression draws the best possible straight line through those dots.…