Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/185454
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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.identifier.urihttp://hdl.handle.net/2445/185454-
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.language.isocatca
dc.rightscc-by-nc-nd (c) Marina Mallol Blay, 2021-
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
dc.rights.accessRightsinfo:eu-repo/semantics/openAccessca
Appears in Collections:Treballs Finals de Grau (TFG) - Matemàtiques

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