Linear regression models a numeric target as a linear combination of the features: y = b0 + b1 x1 + ... The coefficients are estimated by minimizing the sum of squared errors. The model is simple and interpretable, but captures only linear relationships and is sensitive to extreme values.
Example
LinearRegression().fit(X_train, y_train).coef_