Deep learning with PyTorch: a practical approach to building neural network models using PyTorch
Gespeichert in:
1. Verfasser: | |
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Format: | Elektronisch E-Book |
Sprache: | English |
Veröffentlicht: |
Birmingham ; Mumbai
Packt
[February 2018]
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Schlagworte: | |
Online-Zugang: | FHI01 UBY01 UER01 |
Beschreibung: | 1 Online-Ressource (vii, 238 Seiten) Illustrationen, Diagramme (teilweise farbig) |
ISBN: | 9781788626071 |
Internformat
MARC
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100 | 1 | |a Subramanian, Vishnu |e Verfasser |4 aut | |
245 | 1 | 0 | |a Deep learning with PyTorch |b a practical approach to building neural network models using PyTorch |c Vishnu Subramanian |
264 | 1 | |a Birmingham ; Mumbai |b Packt |c [February 2018] | |
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Datensatz im Suchindex
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any_adam_object | |
author | Subramanian, Vishnu |
author_facet | Subramanian, Vishnu |
author_role | aut |
author_sort | Subramanian, Vishnu |
author_variant | v s vs |
building | Verbundindex |
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id | DE-604.BV044999830 |
illustrated | Not Illustrated |
indexdate | 2024-07-10T08:06:36Z |
institution | BVB |
isbn | 9781788626071 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-030391991 |
oclc_num | 1039815526 |
open_access_boolean | |
owner | DE-29 DE-83 DE-573 DE-706 DE-11 |
owner_facet | DE-29 DE-83 DE-573 DE-706 DE-11 |
physical | 1 Online-Ressource (vii, 238 Seiten) Illustrationen, Diagramme (teilweise farbig) |
psigel | ZDB-5-WPSE ZDB-30-PQE ZDB-221-PDA ebook ZDB-221-PDA UBY01_ZDB-221-PDA21 ZDB-30-PQE UER_Einzelkauf |
publishDate | 2018 |
publishDateSearch | 2018 |
publishDateSort | 2018 |
publisher | Packt |
record_format | marc |
spelling | Subramanian, Vishnu Verfasser aut Deep learning with PyTorch a practical approach to building neural network models using PyTorch Vishnu Subramanian Birmingham ; Mumbai Packt [February 2018] © 2018 1 Online-Ressource (vii, 238 Seiten) Illustrationen, Diagramme (teilweise farbig) txt rdacontent c rdamedia cr rdacarrier Deep learning (DE-588)1135597375 gnd rswk-swf PyTorch (DE-588)1202487386 gnd rswk-swf Python Programmiersprache (DE-588)4434275-5 gnd rswk-swf Neural networks (Computer science) Machine learning Python (Computer program language) Artificial intelligence Computers / Intelligence (AI) & Semantics Computers / Neural Networks Neural networks & fuzzy systems Computers / Data Processing Data capture & analysis COMPUTERS / General Electronic books Deep learning (DE-588)1135597375 s Python Programmiersprache (DE-588)4434275-5 s PyTorch (DE-588)1202487386 s DE-604 Erscheint auch als Druck-Ausgabe 978-1-78862-433-6 |
spellingShingle | Subramanian, Vishnu Deep learning with PyTorch a practical approach to building neural network models using PyTorch Deep learning (DE-588)1135597375 gnd PyTorch (DE-588)1202487386 gnd Python Programmiersprache (DE-588)4434275-5 gnd |
subject_GND | (DE-588)1135597375 (DE-588)1202487386 (DE-588)4434275-5 |
title | Deep learning with PyTorch a practical approach to building neural network models using PyTorch |
title_auth | Deep learning with PyTorch a practical approach to building neural network models using PyTorch |
title_exact_search | Deep learning with PyTorch a practical approach to building neural network models using PyTorch |
title_full | Deep learning with PyTorch a practical approach to building neural network models using PyTorch Vishnu Subramanian |
title_fullStr | Deep learning with PyTorch a practical approach to building neural network models using PyTorch Vishnu Subramanian |
title_full_unstemmed | Deep learning with PyTorch a practical approach to building neural network models using PyTorch Vishnu Subramanian |
title_short | Deep learning with PyTorch |
title_sort | deep learning with pytorch a practical approach to building neural network models using pytorch |
title_sub | a practical approach to building neural network models using PyTorch |
topic | Deep learning (DE-588)1135597375 gnd PyTorch (DE-588)1202487386 gnd Python Programmiersprache (DE-588)4434275-5 gnd |
topic_facet | Deep learning PyTorch Python Programmiersprache |
work_keys_str_mv | AT subramanianvishnu deeplearningwithpytorchapracticalapproachtobuildingneuralnetworkmodelsusingpytorch |