Machine Learning based Food Demand Estimation for Restaurants

Abstract

The food industry is critically depending on the accurate forecasting, wide business diversity and cutting edge competence. A wide range of items are included in the stocks. some require particular storage conditions, while others are fast perishable, hence its study serves as the foundation for developing an ideal business model. A food demand forecasting problem is explored in the project, and a machine learning technique is employed as a forecasting tool. The demand for various food products at various places is to be projected for the following weeks using a machine learning approach for discovering recurring patterns inherent in data by learning data repeatedly. Some restaurants in a meal delivery network are in high demand. So that restaurant managers may plan optimal food ingredient storage for proper customer service and waste reduction.