dc.contributor.advisor | Mejía Viteri, José Teodoro | |
dc.contributor.author | Peñafiel Benítez, Narcisa Janeth | |
dc.date.accessioned | 2022-05-18T16:45:17Z | |
dc.date.available | 2022-05-18T16:45:17Z | |
dc.date.issued | 2022 | |
dc.identifier.uri | http://dspace.utb.edu.ec/handle/49000/11644 | |
dc.description | This document is a case study that is oriented with the research subline of the systems engineer career, and the subline is data and telecommunications processes”, its objective is the analysis of the application of machine learning classifiers and the way in which they contribute to science and technology. It is a document clearly related to the study of artificial intelligence and its classification algorithms, and recommends some forms of application that can be deployed and the nature and set of data available for its application. Here, the different existing machine learning methods that are related to classification are analyzed, from the techniques that serve as a basis to the most recent models, with the purpose of finding the best model that makes it possible to know the polarity of an indication. Likewise, it is important to indicate that importance has been given to the participation of systems engineering professionals, who are aware of these aspects related to Artificial Intelligence Machine Learning, to whom an interview has been sent with instruments such as formulations 4 questions extended so that with your opinion this case study is further strengthened with the author's analysis. | es_ES |
dc.description | This document is a case study that is oriented with the research subline of the systems engineer career, and the subline is data and telecommunications processes”, its objective is the analysis of the application of machine learning classifiers and the way in which they contribute to science and technology. It is a document clearly related to the study of artificial intelligence and its classification algorithms, and recommends some forms of application that can be deployed and the nature and set of data available for its application. Here, the different existing machine learning methods that are related to classification are analyzed, from the techniques that serve as a basis to the most recent models, with the purpose of finding the best model that makes it possible to know the polarity of an indication. Likewise, it is important to indicate that importance has been given to the participation of systems engineering professionals, who are aware of these aspects related to Artificial Intelligence Machine Learning, to whom an interview has been sent with instruments such as formulations 4 questions extended so that with your opinion this case study is further strengthened with the author's analysis. | es_ES |
dc.description.abstract | Este documento es un caso de estudio que se orienta con la sublínea de investigación de la carrera de ingeniero de sistemas, y la sublínea es procesos de datos y telecomunicaciones”, tiene como objetivo el análisis de la aplicación de los clasificadores de aprendizaje automático y la forma en la que aportan a la ciencia y tecnología. Es un documento relacionado netamente con el estudio de la inteligencia artificial implica y sus algoritmos de clasificación y recomienda unas formas de aplicación que pueden desplegarse y la naturaleza y el conjunto de datos disponibles para su aplicación. Aquí se analizan los distintos métodos de aprendizaje automático existentes que tienen relación con la clasificación, desde las técnicas que sirven como base hasta los modelos más recientes, con el propósito de encontrar el mejor modelo que posibilite conocer la polaridad de una indicación. Así mismo, es importante indicar que, se ha tomado importancia a la participación de profesionales de ingeniería en sistemas, conocedores de estos aspectos relacionados con Machine Learning de Inteligencia artificial, a los cuales se les ha hecho llegar una entrevista con instrumentos como formulaciones 4 preguntas extendidas para que con su opinión este caso de estudio se fortalezca además con el análisis de la autora. | es_ES |
dc.format.extent | 29 p. | es_ES |
dc.language.iso | es | es_ES |
dc.publisher | Babahoyo: UTB-FAFI. 2022 | es_ES |
dc.rights | Atribución-NoComercial-SinDerivadas 3.0 Ecuador | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/ec/ | * |
dc.subject | Machine Learning | es_ES |
dc.subject | Python | es_ES |
dc.subject | Aprendizaje Automatizado | es_ES |
dc.subject | Inteligencia Artificial | es_ES |
dc.subject | Clasificadores de Aprendizaje | es_ES |
dc.title | Análisis para la aplicación de los clasificadores en el aprendizaje automático. | es_ES |
dc.type | bachelorThesis | es_ES |