Learning TensorFlow: a guide to building deep learning systems
Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks fo...
Gespeichert in:
| Beteiligte Personen: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Sebastopol, CA
O'Reilly Media
2017
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| Ausgabe: | First edition. |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781491978504/?ar |
| Zusammenfassung: | Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision, natural language processing (NLP), speech recognition, and general predictive analytics. Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach to TensorFlow fundamentals for a broad technical audience--from data scientists and engineers to students and researchers. You'll begin by working through some basic examples in TensorFlow before diving deeper into topics such as neural network architectures, TensorBoard visualization, TensorFlow abstraction libraries, and multithreaded input pipelines. Once you finish this book, you'll know how to build and deploy production-ready deep learning systems in TensorFlow. |
| Beschreibung: | Includes index. - Online resource; title from title page (Safari, viewed August 21, 2017) |
| Umfang: | 1 Online-Ressource (1 volume) illustrations |
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| spelling | Hope, Tom VerfasserIn aut Learning TensorFlow a guide to building deep learning systems Tom Hope, Yehezkel S. Resheff, and Itay Lieder First edition. Sebastopol, CA O'Reilly Media 2017 1 Online-Ressource (1 volume) illustrations Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Includes index. - Online resource; title from title page (Safari, viewed August 21, 2017) Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for computer vision, natural language processing (NLP), speech recognition, and general predictive analytics. Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach to TensorFlow fundamentals for a broad technical audience--from data scientists and engineers to students and researchers. You'll begin by working through some basic examples in TensorFlow before diving deeper into topics such as neural network architectures, TensorBoard visualization, TensorFlow abstraction libraries, and multithreaded input pipelines. Once you finish this book, you'll know how to build and deploy production-ready deep learning systems in TensorFlow. TensorFlow (Electronic resource) Machine learning Artificial intelligence Apprentissage automatique Intelligence artificielle artificial intelligence Resheff, Yehezkel S. VerfasserIn aut Lieder, Itay VerfasserIn aut |
| spellingShingle | Hope, Tom Resheff, Yehezkel S. Lieder, Itay Learning TensorFlow a guide to building deep learning systems TensorFlow (Electronic resource) Machine learning Artificial intelligence Apprentissage automatique Intelligence artificielle artificial intelligence |
| title | Learning TensorFlow a guide to building deep learning systems |
| title_auth | Learning TensorFlow a guide to building deep learning systems |
| title_exact_search | Learning TensorFlow a guide to building deep learning systems |
| title_full | Learning TensorFlow a guide to building deep learning systems Tom Hope, Yehezkel S. Resheff, and Itay Lieder |
| title_fullStr | Learning TensorFlow a guide to building deep learning systems Tom Hope, Yehezkel S. Resheff, and Itay Lieder |
| title_full_unstemmed | Learning TensorFlow a guide to building deep learning systems Tom Hope, Yehezkel S. Resheff, and Itay Lieder |
| title_short | Learning TensorFlow |
| title_sort | learning tensorflow a guide to building deep learning systems |
| title_sub | a guide to building deep learning systems |
| topic | TensorFlow (Electronic resource) Machine learning Artificial intelligence Apprentissage automatique Intelligence artificielle artificial intelligence |
| topic_facet | TensorFlow (Electronic resource) Machine learning Artificial intelligence Apprentissage automatique Intelligence artificielle artificial intelligence |
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