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these metrics, we can make predictions using our model and compare them with the actual values: from sklearn.metrics import mean_absolute_error, mean_squared_error # Making predictions y_pred = model.predict(X_test) # Calculating MAE and RMSE mae = mean_absolute_error(y_test, y_pred) rmse =