Countdown header img desk

MAI SUNT 00:00:00:00

MAI SUNT

X

Countdown header img  mob

MAI SUNT 00:00:00:00

MAI SUNT

X

Promotii popup img

Hai la Libris Days!!

CADOURI*, REDUCERI

si Transport gratuit peste 50 lei!

Comanda acum!
Close

Pytorch Pocket Reference: Building and Deploying Deep Learning Models

Pytorch Pocket Reference: Building and Deploying Deep Learning Models - Joe Papa

Pytorch Pocket Reference: Building and Deploying Deep Learning Models


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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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
Citeste mai mult

LIBRIS DAYS

-20%

transport gratuit

108.69Lei

135.86 Lei

Sau 10869 de puncte

!

Fiecare comanda noua reprezinta o investitie pentru viitoarele tale comenzi. Orice comanda plasata de pe un cont de utilizator primeste in schimb un numar de puncte de fidelitate, In conformitate cu regulile de conversiune stabilite. Punctele acumulate sunt incarcate automat in contul tau si pot fi folosite ulterior, pentru plata urmatoarelor comenzi.

Livrare in 3-5 saptamani

Descrierea produsului


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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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
Citeste mai mult

Detaliile produsului

De pe acelasi raft

Parerea ta e inspiratie pentru comunitatea Libris!

Noi suntem despre carti, si la fel este si

Newsletter-ul nostru.

Aboneaza-te la vestile literare si primesti un cupon de -10% pentru viitoarea ta comanda!

*Reducerea aplicata prin cupon nu se cumuleaza, ci se aplica reducerea cea mai mare.

Ma abonez image one
Ma abonez image one