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

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