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DC Field | Value | Language |
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dc.contributor.author | T, Saranya | - |
dc.contributor.author | D, Nivetha | - |
dc.date.accessioned | 2020-09-15T05:15:47Z | - |
dc.date.available | 2020-09-15T05:15:47Z | - |
dc.date.issued | 2018-09 | - |
dc.identifier.isbn | 9-788193-708873 | - |
dc.identifier.uri | http://localhost:8080/xmlui/handle/123456789/1481 | - |
dc.description.abstract | Deep 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 incompatible | en_US |
dc.language.iso | en | en_US |
dc.publisher | PSGR Krishnammal College for Women | en_US |
dc.title | DEEP LEARNING - A LITERATURE SURVEY | en_US |
dc.title.alternative | Recent trends in computing technologies | en_US |
dc.type | Book | en_US |
Appears in Collections: | National Conference |
Files in This Item:
File | Description | Size | Format | |
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DEEP LEARNING - A LITERATURE SURVEY.docx | 10.18 kB | Microsoft Word XML | View/Open |
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