| Description |
1 online resource (584 pages) |
| Summary |
"Deep learning has the reputation as an exclusive domain for math PhDs. Not so. With this book, programmers comfortable with Python will learn how to get started with deep learning right away. Using PyTorch and the fastai deep learning library, you'll learn how to train a model to accomplish a wide range of tasks-including computer vision, natural language processing, tabular data, and generative networks. At the same time, you'll dig progressively into deep learning theory so that by the end of the book you'll have a complete understanding of the math behind the library's functions" -- Provided by publisher. |
| Subject |
Deep learning (Machine learning)
|
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Data mining.
|
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Natural language processing (Computer science)
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Python (Computer program language)
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Apprentissage profond. |
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Exploration de données (Informatique) |
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Traitement automatique des langues naturelles. |
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Python (Langage de programmation) |
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Data mining |
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Deep learning (Machine learning) |
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Natural language processing (Computer science) |
|
Python (Computer program language) |
| Added Author |
Gugger, Sylvain, author.
|
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Nakada, Hidemoto, translator.
|
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中田秀基, translator.
|
| Added Title |
Dīpu rāningu |
|
ディープラーニング |
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Deep learning for coders with fastai and PyTorch : AI applications without a PhD |
| Translation Of: |
Translation of: Howard, Jeremy (Scientist). Deep learning for coders with fastai and PyTorch. First edition. Sebastopol, California : O'Reilly Media, Inc., 2020 9781492045526 (OCoLC)1184463764 |
| ISBN |
9784873119427 (electronic bk.) |
|
4873119421 (electronic bk.) |
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