Joe Papa
PyTorch Pocket Reference: Building and Deploying Deep Learning Models
PyTorch Pocket Reference: Building and Deploying Deep Learning Models
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- More about PyTorch Pocket Reference: Building and Deploying Deep Learning Models
This reference provides clear, structured PyTorch code for neural network development, covering data loading, training loops, model optimization, and GPU/TPU acceleration. It also includes deployment to production and access to useful libraries and the PyTorch ecosystem.
\n Format: Paperback / softback
\n Length: 310 pages
\n Publication date: 21 May 2021
\n Publisher: O'Reilly Media, Inc, USA
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This comprehensive guide offers a valuable resource for anyone seeking to leverage the power of PyTorch for deep learning research and development. Authored by Joe Papa, a renowned expert in the field, it provides direct access to essential syntax, design patterns, and code examples, enabling developers to expedite their projects and minimize the time spent searching for solutions. Whether you are a research scientist, machine learning engineer, or software developer, this guide offers clear, structured PyTorch code that covers every aspect of neural network development, from data loading to customizing training loops, model optimization, and GPU/TPU acceleration.
In a concise and easy-to-understand manner, the guide walks you through the process of deploying your code to production using popular cloud platforms such as AWS, Google Cloud, or Azure. It also demonstrates how to deploy your ML models to mobile and edge devices, ensuring seamless integration into your applications.
By mastering the basic PyTorch syntax and design patterns, you will be able to create custom models and data transforms tailored to your specific needs. The guide provides comprehensive training and deployment strategies using GPUs and TPUs, enabling you to optimize training processes and achieve faster convergence. Additionally, you will gain access to useful PyTorch libraries and the vibrant PyTorch ecosystem, which offers a wide range of tools, resources, and communities to support your deep learning endeavors.
Whether you are a beginner or an experienced practitioner, this guide is an invaluable tool for anyone looking to leverage the capabilities of PyTorch for advanced deep learning applications. With its comprehensive coverage, practical examples, and expert guidance, it empowers developers to push the boundaries of what is possible with this powerful framework. So why wait? Take advantage of this comprehensive guide and unlock the full potential of PyTorch today!
\n Weight: 242g\n
Dimension: 107 x 179 x 20 (mm)\n
ISBN-13: 9781492090007\n \n
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