Programming PyTorch for Deep Learning

Ian Pointer

ISBN 10: 1492045357 / ISBN 13: 9781492045359

Published by O'Reilly Media, US, 2019

About this Item

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

Bibliographic Details

• Title: Programming PyTorch for Deep Learning
• Publisher: O'Reilly Media, US
• Publication Date: 2019
• Language: English
• ISBN 10: 1492045357
• ISBN 13: 9781492045359
• Binding: Paperback
• Condition: New

About this title

Synopsis

Take the next steps toward mastering deep learning, the machine learning method thatâ s transforming the world around us by the second. In this practical book, youâ ll get up to speed on key ideas using Facebookâ 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 PyTorchâ 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

About the Author

Currently Ian is the Director of Partner Engineering at a company called Kogentix that specializes in Machine Learning solutions (including Deep Learning techniques), with multiple Fortune 100 clients. Prior to that, he worked for many years at an early Big Data startup called Mammoth Data, cutting his teeth on Apache Hadoop and Apache Spark. He emigrated to the US from the UK in 2011 and became an American citizen in 2017.