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app.py

@@ -6,7 +6,7 @@ import pandas as pd  # For data manipulation
 from flask import Flask, request, jsonify  # For creating the Flask API
 
 # Initialize Flask app with a name
-superkart_api = Flask("SuperKart’s forecast engine") 
+superkart_api = Flask("SuperKarts forecast engine") 
 
 # Load the trained churn prediction model
 model = joblib.load("backend_files/rf_tuned.joblib") #Complete the code to define the location of the serialized model
@@ -14,7 +14,7 @@ model = joblib.load("backend_files/rf_tuned.joblib") #Complete the code to defin
 # Define a route for the home page
 @superkart_api.get('/')
 def home():
-    return "Welcome to SuperKart’s forecast engine" #Complete the code to define a welcome message
+    return "Welcome to SuperKarts forecast engine" #Complete the code to define a welcome message
 
 # Define an endpoint to predict churn for a single customer
 @superkart_api.post('/v1/predict')