A list of the features of Amazon SageMaker.

Describes the machine learning environments supported by Amazon SageMaker.

Learn how Amazon EC2 provides your instances with public and private IP addresses and DNS hostnames.

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

Connect to your Linux instances with SSH and transfer files to and from your Linux or macOS local machine.

Processing data

Describes Amazon SageMaker projects.

With the SageMaker Model Registry you can catalog models for production, manage model versions, associate metadata, and manage the approval status of a model

Learn about Amazon SageMaker Canvas, a service that you can use to get machine learning predictions and build models without using any code.

SageMaker HyperPod is a capability of SageMaker that provides an always-on machine learning environment on resilient clusters. You can use these clusters to run any machine learning workloads for developing state-of-the-art machine learning models such as large language models (LLMs) and diffusion models.