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In this paper, we look at the use of deep-gaining knowledge of models for sales predictive analytics. The important goal of this paper is to do not forget foremost tactics and case research of using deep getting to know for sales forecasting. The effect of deep learning generalization has been considered. This impact can be used to make sales predictions when there is a small quantity of historical records for specific sales time within the case when a brand new product or keep is launched. A stacking technique for building regression ensemble of single fashions has been studied. The results display that the use of stacking techniques, we will enhance the performance of predictive models for sales time.

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