Getting Started with Amazon SageMaker Studio

By Michael Hsieh
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About this book

Amazon SageMaker Studio is the first integrated development environment for machine learning and is designed to combine data preparation, feature engineering, statistical bias detection, AutoML, training, hosting, ML explainability, monitoring, and MLOps in one environment.

In this book, you’ll start by exploring the features available in Amazon SageMaker Studio to analyze data, develop ML models, and productionize models to meet your goals. As you progress, you will learn how these features work together to address common challenges when building machine learning models in production. Later, you’ll understand how to effectively scale and operationalize the machine learning lifecycle using SageMaker Studio.

By the end of this book, you’ll have learned machine learning best practices with Amazon SageMaker Studio as well as be able to improve productivity in the machine learning development lifecycle and build and deploy models easily for your ML use cases.

Publication date:
April 2022

About the Author

  • Michael Hsieh

    Michael Hsieh is a Senior AI/ML Solutions Architect at Amazon Web Services. He creates and evangelizes ML solutions centered around Amazon SageMaker. He also works with enterprise customers to advance their ML journey.

    Prior to working at AWS, Michael was an advanced analytic consultant creating ML solutions and enterprise level ML strategies at Slalom Consulting in Philadelphia, PA. Prior to consulting, he was a data scientist at University of Pennsylvania Health System focusing on personalized medicine and machine learning research.

    Michael has two master degrees, one in applied physics and one in robotics.

    Originally from Taipei, Taiwan, Michael currently lives in Sammamish, WA, but still roots for Philadelphia Eagles.

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Getting Started with Amazon SageMaker Studio
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