Update app.py

app.py

@@ -18,7 +18,7 @@ from surprise import accuracy
 # Train-test split
 trainset, testset = train_test_split(data, test_size=0.2, random_state=42)
 
-# Train the collaborative filtering model (SVD algorithm for example)
+# train model
 model = SVD()
 model.fit(trainset)
 
@@ -41,7 +41,7 @@ def recommend_laptops(age=None, category=None, gender=None, user_id=None, num_re
         new_user_data['Predicted_Rating'] = new_user_data.apply(lambda row: model.predict(999, row['Laptop_ID']).est, axis=1)
         recommendations = new_user_data.sort_values(by='Predicted_Rating', ascending=False).head(num_recommendations)
 
-    return recommendations[['Laptop_ID', 'Laptop_Name', 'Predicted_Rating']]
+    return recommendations.drop(columns='link')
 
 
 import streamlit as st