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PyTorch Pocket Reference: Building and Deploying Deep Learning Models (Final)

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  • Дата: 15-08-2021, 17:19
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PyTorch Pocket Reference: Building and Deploying Deep Learning Models (Final)Название: PyTorch Pocket Reference: Building and Deploying Deep Learning Models
Автор: Joe Papa
Издательство: O’Reilly Media, Inc.
Год: 2021
Страниц: 310
Язык: английский
Формат: pdf (true), epub
Размер: 10.1 MB, 10.17 MB

Этот краткий, простой в использовании справочник позволяет иметь один из самых популярных фреймворков глубокого обучения для исследований и разработок у вас под рукой. Автор Джо Папа предоставляет мгновенный доступ к синтаксису, шаблонам проектирования и примеры кода, чтобы ускорить вашу разработку и сократить время, которое вы проводите в поиске ответов.

This concise, easy-to-use reference puts one of the most popular frameworks for deep learning research and development at your fingertips. Author Joe Papa provides instant access to syntax, design patterns, and code examples to accelerate your development and reduce the time you spend searching for answers.

Research scientists, machine learning engineers, and software developers will find clear, structured PyTorch code that covers every step of neural network development???from loading data to customizing training loops to model optimization and GPU/TPU acceleration. Quickly learn how to deploy your code to production using AWS, Google Cloud, or Azure and deploy your ML models to mobile and edge devices.

- Learn basic PyTorch syntax and design patterns
- Create custom models and data transforms
- Train and deploy models using a GPU and TPU
- Train and test a deep learning classifier
- Accelerate training using optimization and distributed training
- Access useful PyTorch libraries and the PyTorch ecosystem

Who Should Read This Book:
This book is written for both beginners and advanced users interested in machine learning and AI. It will help to have some experience writing Python code and a basic understanding of data science and machine learning. If you’re just getting started in machine learning, this book will help you learn the basics of PyTorch and provide some simple examples. If you’ve been using another framework, such as TensorFlow, Caffe2, or MXNet, the book with help you become familiar with the PyTorch API and its programming mindset so you can expand your skillset.

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