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app.py

@@ -53,7 +53,9 @@ def predict_rental_price():
     predicted_price = np.exp(predicted_log_price)
 
     # Convert predicted_price to Python float
-    predicted_price = round(float(predicted_price), 2)  # NOTE: Our model (XGBoost) probably returns predictions as NumPy float32 values for efficiency. When you attempt to send these predictions directly within a JSON response, Flask's jsonify function encounters a datatype error
+    predicted_price = round(float(predicted_price), 2)
+    # The conversion above is needed as we convert the model prediction (log price) to actual price using np.exp, which returns predictions as NumPy float32 values.
+    # When we send this value directly within a JSON response, Flask's jsonify function encounters a datatype error
 
     # Return the actual price
     return jsonify({'Predicted Price (in dollars)': predicted_price})