AWS Machine Learning Blog

Category: AWS Identity and Access Management (IAM)

Translate multiple source language documents to multiple target languages using Amazon Translate

Enterprises need to translate business-critical content such as marketing materials, instruction manuals, and product catalogs across multiple languages to communicate with a global audience of customers, partners, and stakeholders. Identifying the source language in each document before calling a translate job creates complexities and adds another step to your workflow. For example, an international product […]

Secure Amazon SageMaker Studio presigned URLs Part 1: Foundational infrastructure

You can access Amazon SageMaker Studio notebooks from the Amazon SageMaker console via AWS Identity and Access Management (IAM) authenticated federation from your identity provider (IdP), such as Okta. When a Studio user opens the notebook link, Studio validates the federated user’s IAM policy to authorize access, and generates and resolves the presigned URL for […]

Enable Amazon SageMaker JumpStart for custom IAM execution roles

With an Amazon SageMaker Domain, you can onboard users with an AWS Identity and Access Management (IAM) execution role different than the Domain execution role. In such case, the onboarded Domain user can’t create projects using templates and Amazon SageMaker JumpStart solutions. This post outlines an automated approach to enable JumpStart for Domain users with […]

Create a cross-account machine learning training and deployment environment with AWS Code Pipeline

A continuous integration and continuous delivery (CI/CD) pipeline helps you automate steps in your machine learning (ML) applications such as data ingestion, data preparation, feature engineering, modeling training, and model deployment. A pipeline across multiple AWS accounts improves security, agility, and resilience because an AWS account provides a natural security and access boundary for your […]