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Deep Learning Pytorch Lightning by Kunal Sawarkar (17 results)
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Deep Learning with PyTorch Lightning: Swiftly build high-performance Artificial Intelligence (AI) models using Python (Paperback or Softback)
Published by Packt Publishing 2/4/2022, 2022
ISBN 10: 180056161X ISBN 13: 9781800561618
Language: English
Paperback or Softback. Condition: New. Deep Learning with PyTorch Lightning: Swiftly build high-performance Artificial Intelligence (AI) models using Python 1.29. Book.
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Deep Learning with PyTorch Lightning: Swiftly build high-performance Artificial Intelligence (AI) models using Python
Published by Packt Publishing 2022-04, 2022
ISBN 10: 180056161X ISBN 13: 9781800561618
Language: English
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Deep Learning with PyTorch Lightning: Swiftly build high-performance Artificial Intelligence (AI) models using Python
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Deep Learning with PyTorch Lightning: Swiftly build high-performance Artificial Intelligence (AI) models using Python
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Deep Learning with PyTorch Lightning: Swiftly build high-performance Artificial Intelligence (AI) models using Python
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Add to basketCondition: New. This deep learning book will introduce you to the basics of PyTorch Lightning and how you can build deep learning models from scratch. You ll learn techniques for building a variety of deep learning debugging models and tuning some of the advanced features .
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Deep Learning with PyTorch Lightning
Published by Packt Publishing Limited, 2022
ISBN 10: 180056161X ISBN 13: 9781800561618
Language: English
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Deep Learning with PyTorch Lightning
Published by Packt Publishing Limited, 2022
ISBN 10: 180056161X ISBN 13: 9781800561618
Language: English
PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.
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Deep Learning with PyTorch Lightning: Build and train high-performance artificial intelligence and self-supervised models using Python
Published by Packt Publishing Limited, 2022
ISBN 10: 180056161X ISBN 13: 9781800561618
Language: English
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
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Add to basketTaschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Build, train, deploy, and scale deep learning models quickly and accurately, improving your productivity using the lightweight PyTorch WrapperKey Features:Become well-versed with PyTorch Lightning architecture and learn how it can be implemented in various industry domainsSpeed up your research using PyTorch Lightning by creating new loss functions, networks, and architecturesTrain and build new algorithms for massive data using distributed trainingBook Description:PyTorch Lightning lets researchers build their own Deep Learning (DL) models without having to worry about the boilerplate. With the help of this book, you'll be able to maximize productivity for DL projects while ensuring full flexibility from model formulation through to implementation. You'll take a hands-on approach to implementing PyTorch Lightning models to get up to speed in no time.You'll start by learning how to configure PyTorch Lightning on a cloud platform, understand the architectural components, and explore how they are configured to build various industry solutions. Next, you'll build a network and application from scratch and see how you can expand it based on your specific needs, beyond what the framework can provide. The book also demonstrates how to implement out-of-box capabilities to build and train Self-Supervised Learning, semi-supervised learning, and time series models using PyTorch Lightning. As you advance, you'll discover how generative adversarial networks (GANs) work. Finally, you'll work with deployment-ready applications, focusing on faster performance and scaling, model scoring on massive volumes of data, and model debugging.By the end of this PyTorch book, you'll have developed the knowledge and skills necessary to build and deploy your own scalable DL applications using PyTorch Lightning.What You Will Learn:Customize models that are built for different datasets, model architectures, and optimizersUnderstand how a variety of Deep Learning models from image recognition and time series to GANs, semi-supervised and self-supervised models can be builtUse out-of-the-box model architectures and pre-trained models using transfer learningRun and tune DL models in a multi-GPU environment using mixed-mode precisionsExplore techniques for model scoring on massive workloadsDiscover troubleshooting techniques while debugging DL modelsWho this book is for:This deep learning book is for citizen data scientists and expert data scientists transitioning from other frameworks to PyTorch Lightning. This book will also be useful for deep learning researchers who are just getting started with coding for deep learning models using PyTorch Lightning. Working knowledge of Python programming and an intermediate-level understanding of statistics and deep learning fundamentals is expected.
