Methods and apparatus for determining item demand and pricing using machine learning processes

Abstract

This application relates to employing trained machine learning processes to predict demands of items during future temporal periods, and to determining a recommended price for the items. For example, a computing device may obtain sales data for an item, and may generate features based on the obtained sales data. The computing device may input the generated features to a trained machine learning process to generate output data characterizing a predicted demand of the item during a future temporal interval. Further, the computing device may determine a recommended price for the item based on the predicted demand and a budget allocation that corresponds to the item. The computing device may store the predicted demand of the item and the recommended price for the item in a data repository.