Pytorch pocket reference: building and deploying deep learning models, joe papa

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Описание

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. \n \nResearch 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. \n

- Learn basic PyTorch syntax and design patterns
\n

- Create custom models and data transforms
\n

- Train and deploy models using a GPU and TPU
\n

- Train and test a deep learning classifier
\n

- Accelerate training using optimization and distributed training
\n

- Access useful PyTorch libraries and the PyTorch ecosystem
\n

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