FINDING NUTRITIOUS ALTERNATIVES TO INGREDIENTS IN RECIPES USING MACHINE LEARNING
by Saachi Subramaniam
Abstract – In the United States, close to 678,000 deaths per year are attributed to nutrition-related causes with obesity and malnutrition as the leading cause of death. By helping users reform their diets, malnutrition in all forms can be combated. This research discusses the factors involved in food nutrition and the integration of nutritious foods into users’ lifestyles. Through the utilization of Python, natural language processing and APIs, this work supplements individuals with nutritional alternatives. In this work, Each ingredient is categorized, and analyzed for nutritional value, then a similar product with higher nutritional value is reported to the user. The work also implements a graphical user interface that allows users to easily interact with the database and obtain results quickly.