Please use this identifier to cite or link to this item: https://repository.iimb.ac.in/handle/2074/19577
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dc.contributor.advisorKumar, U Dinesh
dc.contributor.authorMondal, Ronita
dc.contributor.authorKala, Nilanjan
dc.date.accessioned2021-06-11T14:44:49Z-
dc.date.available2021-06-11T14:44:49Z-
dc.date.issued2020
dc.identifier.urihttps://repository.iimb.ac.in/handle/2074/19577-
dc.description.abstractWe are provided with the historical daily sales data per store per item along with their unit quantity price. The task for our team will be to forecast the total amount of each item that will be sold in each and every shop for the test set. In this submission the objective of the project is to understand the trend of sales from the historical data. After understanding and analysing the data we have to build a model which can be used to forecast the total amount of products that will be sold in each and every shop. The list of shops and the products sold from them change every month. We have to create a robust model which will be able to handle any such situation.
dc.publisherIndian Institute of Management Bangalore
dc.relation.ispartofseriesPGP_CCS_P20_137
dc.subjectFuture sales
dc.subjectSales forecasting
dc.subjectSales management
dc.subjectKaggle
dc.subjectXG Boost
dc.subjectRandom forest
dc.subjectLinear Regression
dc.titlePredicting future sales
dc.typeCCS Project Report-PGP
dc.pages14p.
Appears in Collections:2020
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