Customized Meal Recommendation Using User Preferences and ML Algorithms in Restaurant Systems

The food sector is being revolutionized with tech-based innovations to enhance the customer experience. This paper examines a ”Customized Meal Recommendation System” that uses machine learning algorithms to give personalized meal recommendations based on user preferences such as budget, number of individuals, spice tolerance, and other restaurant-based factors. Three major interfaces exist in the system: User Panel for preference taking, Admin Panel for menu management, and Chef Panel for presenting ordered meals. This research explores technological innovations in personalized meal recommendation and how machine learning is assisting in achieving maximum customer satisfaction with minimal cost.