Linear Regression: A Cornerstone of Machine Learning
Introduction Linear regression is a fundamental statistical method and a powerful tool in machine learning. It's used to model the relationship between a dependent variable and one or more independent variables. In simpler terms, it helps us understand how changes in one variable affect another. How Does Linear Regression Work? Imagine you're trying to predict a house's price based on its square footage. Linear regression would attempt to find the best-fitting line through the data points representing houses of different sizes and their corresponding prices. This line, known as the regression line, represents the linear relationship between the two variables. The equation for a simple linear regression model is: y = mx + b Where: y : The dependent variable (e.g., house price) m : The slope of the line (how much y changes for a unit change in x ) x : The independent variable (e.g., square footage) b : The y-intercept (the value of y when x is 0) Real-World Appli...