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    Learn Amazon SageMaker. A guide to building, training, and deploying machine learning models for developers and data scientists - Second Edition Julien Simon

    (ebook) (audiobook) (audiobook) Książka w języku angielskim
    Learn Amazon SageMaker. A guide to building, training, and deploying machine learning models for developers and data scientists - Second Edition Julien Simon - okladka książki

    Learn Amazon SageMaker. A guide to building, training, and deploying machine learning models for developers and data scientists - Second Edition Julien Simon - okladka książki

    Learn Amazon SageMaker. A guide to building, training, and deploying machine learning models for developers and data scientists - Second Edition Julien Simon - audiobook MP3

    Learn Amazon SageMaker. A guide to building, training, and deploying machine learning models for developers and data scientists - Second Edition Julien Simon - audiobook CD

    Autor:
    Julien Simon
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    554
    Dostępne formaty:
         PDF
         ePub
    Amazon SageMaker enables you to quickly build, train, and deploy machine learning models at scale without managing any infrastructure. It helps you focus on the machine learning problem at hand and deploy high-quality models by eliminating the heavy lifting typically involved in each step of the ML process. This second edition will help data scientists and ML developers to explore new features such as SageMaker Data Wrangler, Pipelines, Clarify, Feature Store, and much more.
    You'll start by learning how to use various capabilities of SageMaker as a single toolset to solve ML challenges and progress to cover features such as AutoML, built-in algorithms and frameworks, and writing your own code and algorithms to build ML models. The book will then show you how to integrate Amazon SageMaker with popular deep learning libraries, such as TensorFlow and PyTorch, to extend the capabilities of existing models. You'll also see how automating your workflows can help you get to production faster with minimum effort and at a lower cost. Finally, you'll explore SageMaker Debugger and SageMaker Model Monitor to detect quality issues in training and production.
    By the end of this Amazon book, you'll be able to use Amazon SageMaker on the full spectrum of ML workflows, from experimentation, training, and monitoring to scaling, deployment, and automation.

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    O autorze książki

    Julien Simon is a Principal Developer Advocate for AI & Machine Learning at Amazon Web Services. He focuses on helping developers and enterprises bring their ideas to life. He frequently speaks at conferences, blogs on the AWS Blog and on Medium, and he also runs an AI/ML podcast.
    Prior to joining AWS, Julien served for 10 years as CTO/VP Engineering in top-tier web startups where he led large Software and Ops teams in charge of thousands of servers worldwide. In the process, he fought his way through a wide range of technical, business and procurement issues, which helped him gain a deep understanding of physical infrastructure, its limitations and how cloud computing can help.

    Packt Publishing - inne książki

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