dc.contributor.advisor | Pinto Cámara, Charles Richard | |
dc.contributor.author | Alonso Gago, Iñigo | |
dc.contributor.other | Master de Ingeniería (Ind902) | |
dc.contributor.other | Ingeniariako Master (Ind902) | |
dc.date.accessioned | 2019-12-04T15:23:48Z | |
dc.date.available | 2019-12-04T15:23:48Z | |
dc.date.issued | 2019-12-04 | |
dc.identifier.uri | http://hdl.handle.net/10810/36690 | |
dc.description.abstract | Machine Learning has already become a game-changer in many fields such as Linguistics, Image Processing or Robotics. Becoming themain research topic for the worldwide specialistsin these fields. On the other hand, other fields such as mechanics are just starting to give baby steps on their path to take full advantage of the benefits that Machine Learning could bring.This work pretends to explore the possibilities of how mechanical engineering problems could benefit from Machine Learning. For this purpose, some of the foundation concepts in Machine Learning and more specifically, in Deep Learning, will be developed. Additionally, an example of how the application of Deep Learning to Mechanics will be provided. | |
dc.language.iso | eng | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | |
dc.subject | machine learning | es_ES |
dc.subject | artitfitial intelligence | |
dc.subject | mechanical engineering | |
dc.subject | deep learning | |
dc.subject | image recognition | |
dc.subject | materials | |
dc.title | Application of Deep Learning to Classification and Regression Problems in Mechanics | es_ES |
dc.type | info:eu-repo/semantics/masterThesis | |
dc.date.updated | 2019-09-10T06:36:22Z | |
dc.language.rfc3066 | es | |
dc.rights.holder | © 2019, el autor | |
dc.identifier.gaurregister | 99779-736013-11 | |
dc.identifier.gaurassign | 88583-736013 | |