Machine Learning Approach for Smart Food Recommendation System

This paper introduces a smart food recommendation system that uses machine learning and user health profiling to suggest meals tailored to individual dietary needs. By considering factors such as age, weight, health conditions, and nutritional goals, the system offers food recommendations that promote well-being. It combines intelligent filtering techniques to align suggestions with both health requirements and user preferences. Unlike conventional systems, it learns from user interactions to refine its results over time.