| # train_and_save_model.py | |
| from sklearn.linear_model import LinearRegression | |
| from sklearn.datasets import make_regression | |
| import joblib | |
| # Generate example data (replace with your own dataset) | |
| X, y = make_regression(n_samples=100, n_features=3, noise=0.1, random_state=42) | |
| # Train the model | |
| model = LinearRegression() | |
| model.fit(X, y) | |
| # Save the model to a file | |
| joblib.dump(model, "linear_regression_model.joblib") | |
| print("Model saved as 'linear_regression_model.joblib'") | |