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Use AWS PrivateLink to set up private access to Amazon Bedrock

AWS Machine Learning Blog

OCTOBER 30, 2023

Amazon Bedrock is a fully managed service provided by AWS that offers developers access to foundation models (FMs) and the tools to customize them for specific applications. The workflow steps are as follows: AWS Lambda running in your private VPC subnet receives the prompt request from the generative AI application.

AWS

AWS ML ML Computer Science

Architecture to AWS CloudFormation code using Anthropic’s Claude 3 on Amazon Bedrock

AWS Machine Learning Blog

SEPTEMBER 27, 2024

Architecting specific AWS Cloud solutions involves creating diagrams that show relationships and interactions between different services. Instead of building the code manually, you can use Anthropic’s Claude 3’s image analysis capabilities to generate AWS CloudFormation templates by passing an architecture diagram as input.

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What’s New in Apache Airflow® 3.0—And How Will It Reshape Your Data Workflows?

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Use Amazon Bedrock tooling with Amazon SageMaker JumpStart models

AWS Machine Learning Blog

DECEMBER 4, 2024

To access SageMaker Studio on the AWS Management Console , you need to set up an Amazon SageMaker domain. You also need an AWS Identity and Access Management (IAM) role with appropriate permissions. About the Author Vivek Gangasani is a Senior GenAI Specialist Solutions Architect at AWS.

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AWS Machine Learning Machine Learning AI

Webinars

What’s New in Apache Airflow® 3.0—And How Will It Reshape Your Data Workflows?

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How VirtuSwap accelerates their pandas-based trading simulations with an Amazon SageMaker Studio custom container and AWS GPU instances

AWS Machine Learning Blog

SEPTEMBER 19, 2023

Prerequisites To run this step-by-step guide, you need an AWS account with permissions to SageMaker, Amazon Elastic Container Registry (Amazon ECR), AWS Identity and Access Management (IAM), and AWS CodeBuild. Complete the following steps: Sign in to the AWS Management Console and open the IAM console.

AWS

AWS Data Science Data Mining Data Mining

Best practices for Meta Llama 3.2 multimodal fine-tuning on Amazon Bedrock

AWS Machine Learning Blog

MAY 1, 2025

Prerequisites To use this feature, make sure that you have satisfied the following requirements: An active AWS account. model customization is available in the US West (Oregon) AWS Region. Sovik Kumar Nath is an AI/ML and Generative AI senior solution architect with AWS. Applied Scientist in AWS Agentic AI. Meta Llama 3.2

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AWS ML ML AI

Fine-tune LLMs with synthetic data for context-based Q&A using Amazon Bedrock

AWS Machine Learning Blog

FEBRUARY 12, 2025

Amazon Bedrock offers a serverless experience, so you can get started quickly, privately customize FMs with your own data, and integrate and deploy them into your applications using AWS tools without having to manage any infrastructure. Our dataset includes Q&A pairs with reference documents regarding AWS services.

AWS

AWS Computer Science Computer Science Deep Learning

Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

AWS Machine Learning Blog

NOVEMBER 9, 2023

Central model registry – Amazon SageMaker Model Registry is set up in a separate AWS account to track model versions generated across the dev and prod environments. with administrative privileges installed on AWS Terraform version 1.5.5 After the key is provisioned, it should be visible on the AWS KMS console.

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AWS ML ML Machine Learning

Manage Amazon SageMaker JumpStart foundation model access with private hubs

AWS Machine Learning Blog

JUNE 21, 2024

Finally, admins can share access to private hubs across multiple AWS accounts, enabling collaborative model management while maintaining centralized control. SageMaker JumpStart uses AWS Resource Access Manager (AWS RAM) to securely share private hubs with other accounts in the same organization.

AWS

AWS Python Machine Learning Machine Learning

Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift

Flipboard

AUGUST 17, 2023

Amazon Redshift uses SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and ML to deliver the best price-performance at any scale. Prerequisites To continue with the examples in this post, you need to create the required AWS resources.

ML ML AWS Data Warehouse

Machine learning with decentralized training data using federated learning on Amazon SageMaker

AWS Machine Learning Blog

AUGUST 22, 2023

In this post, we demonstrate how to use the managed ML platform to provide a notebook experience environment and perform federated learning across AWS accounts, using SageMaker training jobs. You can request a VPC peering connection with another VPC in the same account, or in our use case, connect with a VPC in a different AWS account.

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Machine Learning Machine Learning AWS ML

A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

SEPTEMBER 11, 2024

Examples of other PBAs now available include AWS Inferentia and AWS Trainium , Google TPU, and Graphcore IPU. Around this time, industry observers reported NVIDIA’s strategy pivoting from its traditional gaming and graphics focus to moving into scientific computing and data analytics. Work by Hinton et al.

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Fine-tune Anthropic’s Claude 3 Haiku in Amazon Bedrock to boost model accuracy and quality

AWS Machine Learning Blog

JULY 10, 2024

You can now fine-tune Anthropic Claude 3 Haiku in Amazon Bedrock in a preview capacity in the US West (Oregon) AWS Region. Prerequisites To use this feature, make sure you have satisfied the following requirements: An active AWS account. To request access to the preview, contact your AWS account team or submit a support ticket.

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AWS AI AI ML

Announcing the ODSC East 2023 Keynote Speakers

ODSC - Open Data Science

MAY 1, 2023

.` Hagay Lupesko VP Engineering, MosaicML | Expert in Generative AI Training and Inference, Former Leader at Meta AI and AWS In his role as VP of Engineering, Hagay Lupesko focuses on making generative AI training and inference efficient, fast, and accessible.

Data Science

Data Science Machine Learning Machine Learning Azure

Meet the winners of Phase 2 of the PREPARE Challenge

DrivenData Labs

MAY 1, 2025

changes between 2003 and 2012). I studied Computer Science and really enjoyed the AI space, although hardware resources were always limited, which shaped my push to always simplify. Dawei is an AWS cloud architect in the Data and Security arena, who designs solutions to process big data in real or near realtime manner.

Decision Trees

Decision Trees Clustering Algorithm Machine Learning

Use AWS PrivateLink to set up private access to Amazon Bedrock

Architecture to AWS CloudFormation code using Anthropic’s Claude 3 on Amazon Bedrock

Webinars

Trending Sources

Use Amazon Bedrock tooling with Amazon SageMaker JumpStart models

Webinars

How VirtuSwap accelerates their pandas-based trading simulations with an Amazon SageMaker Studio custom container and AWS GPU instances

Best practices for Meta Llama 3.2 multimodal fine-tuning on Amazon Bedrock

Fine-tune LLMs with synthetic data for context-based Q&A using Amazon Bedrock

Promote pipelines in a multi-environment setup using Amazon SageMaker Model Registry, HashiCorp Terraform, GitHub, and Jenkins CI/CD

Manage Amazon SageMaker JumpStart foundation model access with private hubs

Build ML features at scale with Amazon SageMaker Feature Store using data from Amazon Redshift

Machine learning with decentralized training data using federated learning on Amazon SageMaker

A review of purpose-built accelerators for financial services

Fine-tune Anthropic’s Claude 3 Haiku in Amazon Bedrock to boost model accuracy and quality

Announcing the ODSC East 2023 Keynote Speakers

Meet the winners of Phase 2 of the PREPARE Challenge

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