ToolsThe story, in brief
Accelerate ML feature pipelines with new capabilities in Amazon SageMaker Feature Store
AWS just shipped three new Feature Store capabilities. Here's why your ML pipeline just got faster.
The KeyNews take
Why it matters
Amazon SageMaker Feature Store rolls out developer tooling upgrades (Python SDK v3.8.0) that reduce friction in ML feature pipeline development—a infrastructure-layer play that matters for teams scaling production ML workloads.
The key facts
6 to knowSageMaker Python SDK v3.8.0 released
Three new capabilities announced
Lake Formation governance integration
Iceberg table properties support
Code examples and notebooks provided
Feature pipeline acceleration focus
Go to the source
AWS Machine Learning Blogaws.amazon.com
Publisher excerpt: Today, we’re announcing three new capabilities available in SageMaker Python SDK v3.8.0. In this post, we walk through each capability with code examples you can use to get started. For complete end-to-end walkthroughs, see the accompanying notebooks for Lake Formation governance and Iceberg table…