Programming PyTorch for Deep Learning
Language: English
Published by O'Reilly Media, US, 2019
- Softcover
- New

Seller: Rarewaves USA United, HEBRON, KY, U.S.A.Rarewaves USA United
AbeBooks seller since June 20, 2025
Condition: New
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Add to basketItem description from seller
Take the next steps toward mastering deep learning, the machine learning method that's transforming the world around us by the second. In this practical book, you'll get up to speed on key ideas using Facebook's open source PyTorch framework and gain the latest skills you need to create your very own neural networks.Ian Pointer shows you how to set up PyTorch on a cloud-based environment, then walks you through the creation of neural architectures that facilitate operations on images, sound, text, and more through deep dives into each element. He also covers the critical concepts of applying transfer learning to images, debugging models, and PyTorch in production.Learn how to deploy deep learning models to productionExplore PyTorch use cases from several leading companiesLearn how to apply transfer learning to imagesApply cutting-edge NLP techniques using a model trained on WikipediaUse PyTorch's torchaudio library to classify audio data with a convolutional-based modelDebug PyTorch models using TensorBoard and flame graphsDeploy PyTorch applications in production in Docker containers and Kubernetes clusters running on Google Cloud.…
Seller Inventory # LU-9781492045359
- Title
- Programming PyTorch for Deep Learning
- Author
- Ian Pointer
- Publisher
- O'Reilly Media, US
- Publication year
- 2019
- Condition
- New
- Binding
- Paperback
- Language
- English
- ISBN 10
- 1492045357
- ISBN 13
- 9781492045359
Take the next steps toward mastering deep learning, the machine learning method that’s transforming the world around us by the second. In this practical book, you’ll get up to speed on key ideas using Facebook’s open source PyTorch framework and gain the latest skills you need to create your very own neural networks.
Ian Pointer shows you how to set up PyTorch on a cloud-based environment, then walks you through the creation of neural architectures that facilitate operations on images, sound, text,and more through deep dives into each element. He also covers the critical concepts of applying transfer learning to images, debugging models, and PyTorch in production.
- Learn how to deploy deep learning models to production
- Explore PyTorch use cases from several leading companies
- Learn how to apply transfer learning to images
- Apply cutting-edge NLP techniques using a model trained on Wikipedia
- Use PyTorch’s torchaudio library to classify audio data with a convolutional-based model
- Debug PyTorch models using TensorBoard and flame graphs
- Deploy PyTorch applications in production in Docker containers and Kubernetes clusters running on Google Cloud
"Synopsis" may belong to another edition of this title.
About the Author
He immigrated to the United States from the United Kingdom in 2011 and became an American citizen in 2017.
"About the title" may belong to another edition of this title.
Rarewaves USA United
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