Amazon SageMaker Edge Manager provides model management for edge devices so you can optimize, secure, monitor, and maintain machine learning models on fleets of edge devices such as smart cameras, robots, personal computers, and mobile devices.

Learn about Amazon SageMaker Ground Truth Plus, a turnkey data labeling service that helps you create high-quality labeled datasets.

Get an overview of machine learning (ML), including a typical ML workflow and how to accomplish workflow tasks.

Amazon Q EC2 instance type selector considers your use case, workload type, and CPU manufacturer preference, as well as how you prioritize price and performance. It then uses this data to provide guidance and suggestions for Amazon EC2 instance types that are best suited to your new workloads.

You can assign a security group to an instance when you launch the instance. When you add or remove rules, those changes are automatically applied to all instances to which you've assigned the security group. For more information, see .

Your AWS account automatically has a default security group for the default VPC in each Region. If you don't specify a security group when you launch an instance, the instance is automatically associated with the default security group for the VPC. If you don't want your instances to use the default security group, you can create your own custom security groups and specify them when you launch your instances.

Launch an Amazon EC2 instance, which is a virtual server in the AWS Cloud.

Terminate your instance when you no longer need it and stop incurring charges for that instance.

How to use and share Amazon SageMaker Studio Classic notebooks.

Amazon SageMaker Experiments is a capability of Amazon SageMaker that lets you create, manage, analyze, and compare your machine learning experiments.