Regression Algorithms

Learn regression techniques used to predict continuous values. Understand linear and regularized regression models and their practical applications.

📄️ Linear Regression

Mastering the fundamentals of predicting continuous values using lines, slopes, and intercepts.

Learning to model curved relationships by transforming features into higher-degree polynomials.

Understanding L1 regularization, sparse models, and automated feature selection.

Mastering L2 regularization to prevent overfitting and handle multicollinearity in regression models.

Combining L1 and L2 regularization for the ultimate balance in feature selection and model stability.