Containers for LMI

Install the Apache web server with PHP and MariaDB support on your EC2 instance.

Use a dynamic DNS provider with Amazon EC2 and configure the instance to update the IP address associated with a public DNS name each time the instance starts.

Use Amazon SageMaker built-in algorithms.

Use Amazon SageMaker Assets to provide controlled and regulated access to assets , models or data tables, belonging to your organization. Within SageMaker Assets, users from different AWS accounts can create and share assets related to specific business problems without additional administrator overhead. Instead of having permissions being statically tied to their identity, users can provide permissions to assets that they’re using for their active workflows.

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.

For the AWS Regions supported by Amazon SageMaker and the Amazon Elastic Compute Cloud (Amazon EC2) instance types that are available in each Region, see Amazon SageMaker Pricing .

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

Learn about Amazon Augmented AI (A2I), a service for augmenting AI application labeling with human review loops to boost confidence in datasets.

Select the JupyterLab version to use for an Amazon SageMaker Studio instance.