Linear Regression

Linear Regression is one of the simplest and most widely used algorithms in Machine Learning, particularly for predictive modeling and statistical analysis. It is a supervised learning algorithm that models the relationship between a dependent variable (target) and one or more independent variables (features) using a linear equation.

The mathematical formula for simple linear regression is:

y = mx + b

Where:

• y is the predicted value,
• m is the slope of the line (coefficient),
• x is the input feature,
• b is the intercept.

Linear Regression is efficient for tasks like price prediction, sales forecasting, and risk assessment.