Machine Learning based Diet Recommendation System

Recent studies have shown that food recommendation systems can contribute well enough in the field of food and nutrition. Such systems are based on machine learning models, offer personalized diet and food recommendations depending on a person’s dietary preferences, health needs and fitness goals. This review talks about a Diet Recommendation System that produces custom diet plans based on age, gender, height, weight, health conditions, food preferences and specific nutritional needs. For data collection we have used USDA and grocery datasets. Collaborative and content-based filtering methods are used for building recommendation models. Algorithms like decision trees and random forest are used for model training. The recommends a diet plan for the day based on user inputs. This application will help users in planning their everyday meals which may vary due to food choices, nutritional requirements and health conditions.