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app.py

@@ -30,7 +30,7 @@ def predict_churn():
     input_data = pd.DataFrame([sample])
     
     prediction = model.predict(input_data).tolist()[0]
-    print("*********************** Prediction: ", prediction, file=sys.err)
+    print("*********************** Prediction: ", prediction, file=sys.stderr)
 
     prediction_label = 'churn' if prediction == 1 else 'not churn'