Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/1481
Full metadata record
DC FieldValueLanguage
dc.contributor.authorT, Saranya-
dc.contributor.authorD, Nivetha-
dc.date.accessioned2020-09-15T05:15:47Z-
dc.date.available2020-09-15T05:15:47Z-
dc.date.issued2018-09-
dc.identifier.isbn9-788193-708873-
dc.identifier.urihttp://localhost:8080/xmlui/handle/123456789/1481-
dc.description.abstractDeep Learning is a subfield of machine learning concerned with algorithms inspired by the structure and function of the brain called artificial neural networks. Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on learning data representations, learning can be supervised, semi-supervised or unsupervised. Deep learning models are vaguely inspired by information processing and communication patterns in biological nervous systems yet have various differences from the structural and functional properties of biological brains, which make them incompatibleen_US
dc.language.isoenen_US
dc.publisherPSGR Krishnammal College for Womenen_US
dc.titleDEEP LEARNING - A LITERATURE SURVEYen_US
dc.title.alternativeRecent trends in computing technologiesen_US
dc.typeBooken_US
Appears in Collections:National Conference

Files in This Item:
File Description SizeFormat 
DEEP LEARNING - A LITERATURE SURVEY.docx10.18 kBMicrosoft Word XMLView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.