Please use this identifier to cite or link to this item:
https://repository.iimb.ac.in/handle/2074/19577
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Kumar, U Dinesh | |
dc.contributor.author | Mondal, Ronita | |
dc.contributor.author | Kala, Nilanjan | |
dc.date.accessioned | 2021-06-11T14:44:49Z | - |
dc.date.available | 2021-06-11T14:44:49Z | - |
dc.date.issued | 2020 | |
dc.identifier.uri | https://repository.iimb.ac.in/handle/2074/19577 | - |
dc.description.abstract | We 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.publisher | Indian Institute of Management Bangalore | |
dc.relation.ispartofseries | PGP_CCS_P20_137 | |
dc.subject | Future sales | |
dc.subject | Sales forecasting | |
dc.subject | Sales management | |
dc.subject | Kaggle | |
dc.subject | XG Boost | |
dc.subject | Random forest | |
dc.subject | Linear Regression | |
dc.title | Predicting future sales | |
dc.type | CCS Project Report-PGP | |
dc.pages | 14p. | |
Appears in Collections: | 2020 |
Files in This Item:
File | Size | Format | |
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PGP_CCS_P20_137.pdf | 1.23 MB | Adobe PDF | View/Open Request a copy |
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