Food Recommendation System Based on Mood of the User

Living in the twenty-first century we are provided with many services to tackle our hunger cravings, but the abundance of these services in this era has put humankind into a great dilemma of 'What to Eat?' Many of us just keep scrolling within the options and end by choosing nothing. In the food business, machine learning and artificial intelligence applications are increasingly extensive. This paper presents the recommendation system using hybrid filtering approach to recommend dishes and the recipes based on the mood. Existing recommendation system does not recommend food based on the hormonal changes at a particular mood. The proposed system provides the personalization to the user. A website is designed to give suggestions to the users of food according to their mood which will save time. This model is connected to the Django REST framework.