Machine Learning
Linear Regression
The simplest regression algorithm that models the relationship between input features and a continuous output as a straight line (or hyperplane in multiple dimensions). It minimizes the sum of squared errors.
Why It Matters
Linear regression is the foundation of predictive analytics. While simple, it is still widely used in business for forecasting, trend analysis, and understanding relationships between variables.
Example
Predicting house prices based on square footage: Price = $200 × SquareFootage + $50,000. For a 2,000 sqft house, the predicted price is $450,000.
Think of it like...
Like drawing the best-fit line through a scatter plot of data points — it captures the overall trend even if individual points do not fall exactly on the line.