Getting Started with Amazon SageMaker Studio
- Paperback: 326 pages
- Publisher: WOW! eBook (March 31, 2022)
- Language: English
- ISBN-10: 1801070156
- ISBN-13: 978-1801070157
Getting Started with Amazon SageMaker Studio: Build production-grade machine learning models with Amazon SageMaker Studio, the first integrated development environment in the cloud, using real-life machine learning examples and code
Amazon SageMaker Studio is the first integrated development environment (IDE) for machine learning (ML) and is designed to integrate ML workflows: data preparation, feature engineering, statistical bias detection, automated machine learning (AutoML), training, hosting, ML explainability, monitoring, and MLOps in one environment.
In this Getting Started with Amazon SageMaker Studio 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 ML models in production. After that, you’ll understand how to effectively scale and operationalize the ML life cycle using SageMaker Studio.
- Explore the ML development life cycle in the cloud
- Understand SageMaker Studio features and the user interface
- Build a dataset with clicks and host a feature store for ML
- Train ML models with ease and scale
- Create ML models and solutions with little code
- Host ML models in the cloud with optimal cloud resources
- Ensure optimal model performance with model monitoring
- Apply governance and operational excellence to ML projects
By the end of this Getting Started with Amazon SageMaker Studio book, you’ll have learned ML best practices regarding Amazon SageMaker Studio, as well as being able to improve productivity in the ML development life cycle and build and deploy models easily for your ML use cases.
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