Introduction
Discover the fundamentals of Linear Regression, a foundational algorithm for predicting continuous values in machine learning.
Theory
Explore the mathematical principles of Linear Regression, including Ordinary Least Squares and Gradient Descent.
scikit-learn Example
Fit and evaluate an ordinary least-squares model without leaking test information.
TensorFlow Example
Train a one-layer TensorFlow regression model on deterministic local data.
PyTorch Example
Train a one-layer regression model with PyTorch using deterministic local data.
Common Mistakes & Best Practices
Avoid leakage, unsupported inference, unstable coefficients, and misleading regression evaluation.
Comparison with Other Algorithms
Compare linear regression with trees, nearest neighbors, support-vector regression, and neural networks.