Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.12104/92380
Title: | Machine Learning model for managing risk on Procurement Contracts |
Author: | Toribio Nava, José Luis |
metadata.dc.contributor.director: | Salazar Linares, Pablo |
Advisor/Thesis Advisor: | Parra González, Ezra Federico Maciel Arellano, María Del Rocío Larios Rosillo, Víctor Manuel |
Keywords: | Machine Learning;Artificial Intelligence;Business Intelligence. |
Issue Date: | 11-Jul-2022 |
Publisher: | Biblioteca Digital wdg.biblio Universidad de Guadalajara |
Abstract: | In current time, the process of making decisions in companies through the data is an important task to be competitive Worldwide. One of the most important areas inside companies is the Procurement department. This area usually has a huge amount of contracts due to, the hight number of agreement with suppliers, that may make business with them. To analyze contracts for making the purchase decisions or verify the contracts to identify any risk usually the purchase process is a manual and exhausting process that may take a lot of time to the contract analysts. These exhaustive and manual process can be reduce through implementing Artificial intelligence (AI) approaches. The AI has many branches of study; however, in the current project, in this work we will focus on Machine learning (ML) techniques, where we present a proposal to develop and implement a model training that includes ML techniques to identify risk, and according to this approach we are able to make the right decisions through Business Intelligence (BI). |
URI: | https://wdg.biblio.udg.mx https://hdl.handle.net/20.500.12104/92380 |
metadata.dc.degree.name: | MAESTRIA EN CIENCIA DE LOS DATOS |
Appears in Collections: | CUCEA |
Files in This Item:
File | Size | Format | |
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MCUCEA10903FT.pdf | 2.29 MB | Adobe PDF | View/Open |
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