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Customize Amazon SageMaker Studio using Lifecycle Configurations


Amazon SageMaker Studio is a web-based, integrated development environment (IDE) for machine learning (ML) that lets you build, train, debug, deploy, and monitor your ML models. It provides all the tools you need to take your models from experimentation to production while boosting your productivity. You can write code, track experiments, visualize data, and perform debugging and monitoring within a single, integrated visual interface.
We’re excited to announce Lifecycle Configuration for Studio, a new capability that enables developers to automate customization for your Studio development environments.
Lifecycle configurations are shell scripts triggered by Studio lifecycle events, such as starting …

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