INVENTORY FORECASTING USING MACHINE LEARNING ALGORITHM

Abstract

Day by day supply chain is becoming more and more competitive. It is now necessary for organizations to accurately predict their customers' behaviour to deal with unexpected surges and lulls in the demand of the product. With new methods of data collection coming up the volume of data generated is large in number as well as in variety. So, it becomes difficult for traditional methods to make forecasts, for the same reason, the idea of using more advanced Machine Learning techniques is being explored. Here for my dissertation, I will be making use of such techniques Long Short-Term Memory and SARIMA for predicting the sales of products in retail stores because of their better capabilities of handling time series data.