Machine Learning Workflows in IAM-based domains
Amazon SageMaker Unified Studio provides a comprehensive machine learning environment within IAM-based domains that enables you to discover, deploy, and manage machine learning models through a unified interface.
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Discover Foundation Models and Registered Models from multiple model providers, easily deploy them using sample notebooks
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Customize foundation models using Jupyterlab IDE or Data Notebooks, a new serverless Notebook for ML Practitioners
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Create and track Experiments and identify the best model for your usecase using MLflow
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Use Agentic AI is Notebooks to easily create and train models
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Monitor training jobs and model performance metrics
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Manage model lifecycle through the integrated model registry
The machine learning capabilities in Amazon SageMaker Unified Studio integrate seamlessly with your project's IAM permissions and compute resources, providing secure access to models and deployment infrastructure within your domain's governance framework.
