Learn Amazon SageMaker – Second Edition

Learn Amazon SageMaker, 2nd Edition

eBook Details:

  • Paperback: 554 pages
  • Publisher: WOW! eBook; 2nd edition (November 26, 2021)
  • Language: English
  • ISBN-10: 1801817952
  • ISBN-13: 978-1801817950

eBook Description:

Learn Amazon SageMaker, 2nd Edition: Swiftly build and deploy machine learning models without managing infrastructure and boost productivity using the latest Amazon SageMaker capabilities such as Studio, Autopilot, Data Wrangler, Pipelines, and Feature Store

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 Learn Amazon SageMaker, 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 Learn Amazon SageMaker, 2nd Edition 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.

  • Become well-versed with data annotation and preparation techniques
  • Use AutoML features to build and train machine learning models with AutoPilot
  • Create models using built-in algorithms and frameworks and your own code
  • Train computer vision and natural language processing (NLP) models using real-world examples
  • Cover training techniques for scaling, model optimization, model debugging, and cost optimization
  • Automate deployment tasks in a variety of configurations using SDK and several automation tools

By the end of this Learn Amazon SageMaker, 2nd Edition 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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