Learn how to use shared spaces for collaboration between all users in a SageMaker domain.

Create, store, and share features with Amazon SageMaker Feature Store.

Amazon SageMaker Model Monitor continuously monitors the quality of Amazon SageMaker machine learning models in production.

Use Amazon SageMaker Model Card to document critical details about your machine learning (ML) models for governance and reporting.

Amazon SageMaker smart sifting is a capability of SageMaker Training that helps improve the efficiency of training datasets and reduce total training time and cost.

RStudio on Amazon SageMaker is an integrated development environment for R with a console, syntax-highlighting editor that supports direct code execution, and tools for plotting, history, debugging and workspace management.

Use Amazon SageMaker built-in algorithms or pretrained models to quickly get started with fine-tuning or deploying models for specific tasks.

Learn how to deploy your machine learning models for real-time inference using SageMaker hosting services. Includes information about the options available.

Learn about Amazon SageMaker, including information for first-time users.

List of features offered by Amazon SageMaker: new features, machine learning environments, and major features.