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
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
PyTorch Pocket Reference: Building and Deploying Deep Learning Models
307
PyTorch Pocket Reference: Building and Deploying Deep Learning Models
307
Product Details
| ISBN-13: | 9781492090007 |
|---|---|
| Publisher: | O'Reilly Media, Incorporated |
| Publication date: | 06/15/2021 |
| Pages: | 307 |
| Product dimensions: | 4.25(w) x 7.00(h) x (d) |