Programming PyTorch for Deep Learning (Paperback)

Ian Pointer

ISBN 10: 1492045357 / ISBN 13: 9781492045359

Verlag: O'Reilly Media, Sebastopol, 2019

Beschreibung

Paperback. 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" Take the next steps toward mastering deep learning, the machine learning method thats transforming the world around us by the second. In this practical book, youll get up to speed on key ideas using Facebooks open source PyTorch framework and gain the latest skills you need to create your very own neural networks. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9781492045359

Bibliografische Details

Titel: Programming PyTorch for Deep Learning (...

Verlag: O'Reilly Media, Sebastopol

Erscheinungsdatum: 2019

Einband: Paperback

Zustand: new

Über diesen Titel

Reseña del editor:

Deep Learning has the potential to change everything in the computer world. Already, in just a few short years, it has surpassed traditional computer vision techniques and it's starting to do the same with NLP. Google is integrating Deep Learning in all aspects of its operations, down to orchestrating jobs in their data centers and even replacing some traditional data structures. But there's still a lack of developers out there with the ability to bring Deep Learning to their domain, and many of the introductions to the subject are weighed down in the mathematical concepts. This book will provide a primer that should allow a developer to get started using these powerful new techniques to bear on almost any data that they have to hand.