Update app.py

app.py

@@ -4,10 +4,10 @@ import sklearn
 from sklearn.metrics.pairwise import cosine_similarity
 
 # Load movie metadata into a pandas DataFrame
-movie_data = pd.read_csv('/content/drive/MyDrive/kaggle/movies_metadata.csv', usecols=['title', 'budget', 'revenue', 'vote_count', 'vote_average'])
+movie_data = pd.read_csv('movies_metadata.csv', usecols=['title', 'budget', 'revenue', 'vote_count', 'vote_average'])
 
 # Load movie ratings into a pandas DataFrame
-ratings_data = pd.read_csv('/content/drive/MyDrive/kaggle/ratings_small.csv')
+ratings_data = pd.read_csv('ratings_small.csv')
 
 # Collaborative Filtering
 def collaborative_filtering(user_id, num_recommendations=5):