L'algorisme de retropropagació d'errors des d'un punt de vista matemàtic

dc.contributor.advisorBosch Gual, Miquel
dc.contributor.authorMallol Blay, Marina
dc.date.accessioned2022-05-09T08:08:43Z
dc.date.available2022-05-09T08:08:43Z
dc.date.issued2021-06-20
dc.descriptionTreballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2021, Director: Miquel Bosch Gualca
dc.description.abstract[en] In this project, we are going to study the backpropagation algorithm from a mathematical perspective and analize why this algorithm, which was forgotten in the past, is now used in supervised learning in order to train artificial neural networks. First of all we will talk about how artificial neural networks are organized and how they work. Next, we will study the gradient descend method, the Newton’s method, and other methods, used in learning. Finally, we will see how the backpropagation algorithm works and the calculations derived from it.ca
dc.format.extent43 p.
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/2445/185454
dc.language.isocatca
dc.rightscc-by-nc-nd (c) Marina Mallol Blay, 2021
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.sourceTreballs Finals de Grau (TFG) - Matemàtiques
dc.subject.classificationXarxes neuronals (Informàtica)ca
dc.subject.classificationTreballs de fi de grau
dc.subject.classificationAprenentatge automàticca
dc.subject.classificationAlgorismes computacionalsca
dc.subject.otherNeural networks (Computer science)en
dc.subject.otherBachelor's theses
dc.subject.otherMachine learningen
dc.subject.otherComputer algorithmsen
dc.titleL'algorisme de retropropagació d'errors des d'un punt de vista matemàticca
dc.typeinfo:eu-repo/semantics/bachelorThesisca

Fitxers

Paquet original

Mostrant 1 - 1 de 1
Carregant...
Miniatura
Nom:
tfg_marina_mallol_blay.pdf
Mida:
5.1 MB
Format:
Adobe Portable Document Format
Descripció:
Memòria