Smart Budget and Location-Based Hotel & Restaurant Recommendation System

The increasing number of restaurants and hotels has made it difficult for users to choose the best option that fits their budget and location. Most existing food and travel applications emphasize popularity and ratings, but they often ignore budget-friendly recommendations. To address this issue, we propose Frugal Foodie, a hotel and restaurant recommendation system focused on affordability and convenience. The system accepts user inputs such as budget and search radius, along with two location modes: current location (GPS-based) or manual area entry. The collected dataset is pre-processed using Pandas for cleaning and feature extraction, and recommendations are generated through K-Means clustering, which groups restaurants and hotels