🚀 Master Regression 2025! 🚀

Regression Type	Explanation	Equation	Use Case Example
Simple Linear Regression	One independent variable, one dependent variable	`y = β₀ + β₁·x + ε`	Predicting house price based on square footage
Multiple Linear Regression	Multiple independent variables	`y = β₀ + β₁·x₁ + β₂·x₂ + ... + βₙ·xₙ + ε`	Forecasting sales revenue based on marketing metrics
Polynomial Regression	Fits a nonlinear curve using polynomial terms	`y = β₀ + β₁·x + β₂·x² + ...`	Modeling population growth over time
Ridge Regression	Prevents overfitting by shrinking coefficients (L2)	`Minimize: ∑(yᵢ - ŷᵢ)² + α∑βⱼ²`	Stock prediction with many similar features
Lasso Regression	Performs feature selection by shrinking some coefficients to 0 (L1)	`Minimize: ∑(yᵢ - ŷᵢ)² + α∑\|βⱼ\|`	Detecting major factors in customer churn
Elastic Net	Combines Ridge and Lasso for balanced regularization	`Minimize: ∑(yᵢ - ŷᵢ)² + α₁∑\|βⱼ\| + α₂∑βⱼ²`	Analyzing genetics with correlated predictors