Amazon SageMaker simplifies setting up SageMaker domain for enterprises to onboard their users to SageMaker

Package and deploy classical ML and LLMs easily with Amazon SageMaker, part 2: Interactive User Experiences in SageMaker Studio

Package and deploy classical ML and LLMs easily with Amazon SageMaker, part 1: PySDK Improvements

New – Code Editor, based on Code-OSS VS Code Open Source now available in Amazon SageMaker Studio

Scale foundation model inference to hundreds of models with Amazon SageMaker – Part 1

Reduce model deployment costs by 50% on average using the latest features of Amazon SageMaker

Minimize real-time inference latency by using Amazon SageMaker routing strategies

Build and evaluate machine learning models with advanced configurations using the SageMaker Canvas model leaderboard

Introducing Amazon SageMaker HyperPod to train foundation models at scale

Accelerate data preparation for ML in Amazon SageMaker Canvas