An Efficient Novel Approach on Machine Learning Paradigmsfor Food Delivery Company through Demand Forecastıng in societal community

Department of Information and Technology, Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad, India

^* Corresponding Author: subbu.griet@gmail.com

Abstract

A food delivery business must be able to accurately forecast demand on a daily and weekly basis since it deals with a lot of perishable raw components. A warehouse that keeps too much inventory runs the danger of wasting items, whereas a warehouse that maintains too little inventory runs the risk of running out of stock, which might lead consumers to switch to your competitors. Planning for purchasing is essential because most raw materials are perishable and delivered on a weekly basis. For this issue to be resolved, demand forecasting is crucial. With the aid of historical data-driven predictive research, demand forecasting determines and forecasts future consumer demand for a good or service. By predicting future sales and revenues, demand forecasting assists the organisation in making more educated supply decisions. Regression methods like linear regression, decision trees, and Xgboost are used to overcome this issue.