AN EFFECTIVE AND REAL TIME PRODUCT DEMAND FORECASTING MODEL USING ML









Abstract

In today's environment, business intelligence (BI) is crucial in developing a strategy and implementing datadriven activities. Business intelligence (BI) is a vital component of a decision support system that assists an organization in analyzing data and making choices throughout the business process. To estimate future company demands, machine learning is applied. One of the most crucial parts of commercial decision-making is demand prediction. For demand forecasting, sales data which are not pre-processed is received from the market and future sales/product demands are predicted based on the data. This forecast is based on data collected from a number of sources. On a weekly, monthly, and quarterly basis, to assess goods/commodity demand, the machine learning techniques examines data from a variety of sources. In estimation of demand, accurate precision is not negotiable, the high precise the model of the system, the high efficient it is. In addition, by comparing planned and actual data and determining the proportion of inaccuracy, this study will assess efficiency


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Algorithms


Software And Hardware