Paper Title
Machine Learning in Demand Forecasting for Retail

This article presents a strategy for anticipating consumer demand based on essential indicators and the target variable. These models are based on traditional and contemporary techniques for predicting time series. Our proposed demand forecasting model is based on working with panel samples, clustering time series that are generated based on starting data of economic factors, and using machine learning techniques. The proposed models were tested using conventional regression performance metrics. Keywords - Machine Learning, Forecasting, Recommendation System, Retail Demand