Tomasz Palczewski, Jaejun Lee (Brandon), Lenin Mookiah

Production-Ready Applied Deep Learning (eBook, ePUB)

Learn how to construct and deploy complex models in PyTorch and TensorFlow deep learning frameworks

• Format: ePub

Produktbeschreibung

Machine learning engineers, deep learning specialists, and data engineers encounter various problems when moving deep learning models to a production environment. The main objective of this book is to close the gap between theory and applications by providing a thorough explanation of how to transform various models for deployment and efficiently distribute them with a full understanding of the alternatives.
First, you will learn how to construct complex deep learning models in PyTorch and TensorFlow. Next, you will acquire the knowledge you need to transform your models from one framework to the other and learn how to tailor them for specific requirements that deployment environments introduce. The book also provides concrete implementations and associated methodologies that will help you apply the knowledge you gain right away. You will get hands-on experience with commonly used deep learning frameworks and popular cloud services designed for data analytics at scale. Additionally, you will get to grips with the authors' collective knowledge of deploying hundreds of AI-based services at a large scale.
By the end of this book, you will have understood how to convert a model developed for proof of concept into a production-ready application optimized for a particular production setting.

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Produktdetails

• Verlag: Packt Publishing
• Seitenzahl: 322
• Erscheinungstermin: 30. August 2022
• Englisch
• ISBN-13: 9781803238050
• Artikelnr.: 70224908

Autorenporträt

Tomasz Palczewski is currently working as a staff software engineer at Samsung Research America. He has a Ph.D. in physics and an eMBA degree from Quantic. His zeal for getting insights out of large datasets using cutting-edge techniques led him to work across the globe at CERN (Switzerland), LBNL (Italy), J-PARC (Japan), University of Alabama (US), and University of California (US). In 2016, he was deployed to the South Pole to calibrate the world's largest neutrino telescope. Later, he decided to pivot his career and focus on applying his skills in industry. Currently, he works on modeling user behavior and creating value for advertising and marketing verticals by deploying machine learning (ML), deep learning, and statistical models at scale.