Abstract: A streamlined nutrition tracking application can provide user devices with access to a user interface that enables a user to input simplified information corresponding to a food or beverage the user consumes. This simplified input can be made possible in part by a backend system's streamlined nutrition tracking component, which can simplify nutritional information obtained from an USDA (Food and Drug Administration) database. A machine learning component can improve the accuracy of users' simplified inputs over time, based on the aggregated inputs of many users. The application can access the machine learning component to request an adjustment of the user food consumption input based on aggregated machine learning of user food consumption inputs of a plurality of users. The application can output nutritional performance data to the user based on the machine learning, the user's basic metabolic rate, and/or lifestyle factors, as a graph or chart that indicates nutritional consumption of the user over time.