Please use this identifier to cite or link to this item:
http://hdl.handle.net/10609/74565
Title: | Predicción de ventas de comestibles corporación favorita |
Author: | Kreplak, Gabriel |
Director: | Sancho-Vinuesa, Teresa Pujol-Jover, Maria |
Tutor: | Subirats, Laia |
Others: | Universitat Oberta de Catalunya |
Abstract: | The goal of this final grade project is to earn a relevant score in the Kaggle¿s competition: Corporación Favorita Grocery Sales Forecasting through building a state of the art predictive model aimed to forecast future sales. Corporación Favorita has challenged the Kaggle community to build a model that more accurately forecasts product sales. They currently rely on subjective forecasting methods with very little data to back them up and very little automation to execute plans. They¿re excited to see how machine learning could better ensure they please customers by having just enough of the right products at the right time. |
Keywords: | predictive models data analysis business intelligence sales Big data -- TFM |
Document type: | info:eu-repo/semantics/masterThesis |
Issue Date: | 22-Jan-2018 |
Publication license: | http://creativecommons.org/licenses/by-nc-nd/3.0/es/ |
Appears in Collections: | Bachelor thesis, research projects, etc. |
Files in This Item:
File | Description | Size | Format | |
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gkreplakTFM0118memoria.pdf | Memoria del TFM | 1,87 MB | Adobe PDF | View/Open |
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