Remove 2012 Remove Data Scientist Remove ML
article thumbnail

Scale ML workflows with Amazon SageMaker Studio and Amazon SageMaker HyperPod

AWS Machine Learning Blog

Scaling machine learning (ML) workflows from initial prototypes to large-scale production deployment can be daunting task, but the integration of Amazon SageMaker Studio and Amazon SageMaker HyperPod offers a streamlined solution to this challenge. ML SA), Monidipa Chakraborty (Sr. Delete the IAM role you created.

ML 101
article thumbnail

Implement user-level access control for multi-tenant ML platforms on Amazon SageMaker AI

AWS Machine Learning Blog

Managing access control in enterprise machine learning (ML) environments presents significant challenges, particularly when multiple teams share Amazon SageMaker AI resources within a single Amazon Web Services (AWS) account. In such cases, the sagemaker:DomainId and sagemaker:UserProfileName keys can be used to place this restriction.

ML 61
professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Configure fine-grained access to Amazon Bedrock models using Amazon SageMaker Unified Studio

AWS Machine Learning Blog

Launched in 2025, SageMaker Unified Studio is a single data and AI development environment where you can find and access the data in your organization and act on it using the best tools across use cases. To manage data access, you can adjust the IAM permissions tied to the project’s role.

AWS 81
article thumbnail

Import data from Google Cloud Platform BigQuery for no-code machine learning with Amazon SageMaker Canvas

AWS Machine Learning Blog

In the modern, cloud-centric business landscape, data is often scattered across numerous clouds and on-site systems. This fragmentation can complicate efforts by organizations to consolidate and analyze data for their machine learning (ML) initiatives.

article thumbnail

Intelligent document processing at scale with generative AI and Amazon Bedrock Data Automation

Flipboard

About the authors Nikita Kozodoi, PhD , is a Senior Applied Scientist at the AWS Generative AI Innovation Center, where he works on the frontier of AI research and business. With rich experience in Generative AI and diverse areas of ML, Nikita is enthusiastic about using AI to solve challenging real-world business problems across industries.

AWS 130
article thumbnail

Use Amazon Bedrock tooling with Amazon SageMaker JumpStart models

AWS Machine Learning Blog

SageMaker JumpStart helps you get started with machine learning (ML) by providing fully customizable solutions and one-click deployment and fine-tuning of more than 400 popular open-weight and proprietary generative AI models. Before this role, he obtained an MS in Computer Science from NYU Tandon School of Engineering.

AWS 105
article thumbnail

Fine-tune multimodal models for vision and text use cases on Amazon SageMaker JumpStart

AWS Machine Learning Blog

jpg", "prompt": "Which part of Virginia is this letter sent from", "completion": "Richmond"} SageMaker JumpStart SageMaker JumpStart is a powerful feature within the SageMaker machine learning (ML) environment that provides ML practitioners a comprehensive hub of publicly available and proprietary foundation models (FMs).

ML 108