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