Smart Recommendation System

Develop a robust backend system capable of providing personalized recommendations for products or places. This system will analyze user preferences, historical behavior, and current location data to suggest relevant items. The project involves designing and implementing scalable APIs, integrating with various data sources, developing and optimizing recommendation algorithms (e.g., collaborative filtering, content-based filtering), and managing a flexible database to store user profiles, item data, and interaction logs. The goal is to create a highly personalized and dynamic user experience by continuously refining recommendation logic based on real-time user interactions.