Posted On: Mar 18, 2021

We’re excited to announce that Amazon SageMaker Feature Store is now available in the Amazon Web Services China (Beijing) Region, operated by Sinnet and Amazon Web ServicesChina (Ningxia) Rregion, operated by NWCDs (Beijing, Ningxia). Amazon SageMaker Feature Store is a feature of Amazon SageMaker that ingests, stores, shares, reuses, and serves features for real time and batch machine learning (ML) applications.  

In machine learning, features are data signals that ML models rely on to make accurate predictions. During training, features are stored in batches to train multiple variations. The same features need to be available in real-time during inference for accurate predictions. Maintaining consistency between training and inference is challenging and may lead to inaccurate predictions or require additional coding.

Amazon SageMaker Feature Store is a fully managed repository that helps maintain consistency between features used at the time of inference and model training, so you can confidently deploy models in production with more predictable behavior allowing you to operate ML models at scale. Amazon SageMaker Feature Store enables metadata management and discovery of features with easy tagging and search, so data science teams can simply reuse an existing feature instead of having to rewrite and process features for each new model. For real time predictions, features can be served with low millisecond latency or extracted for model training or batch prediction use cases from the feature store. Amazon SageMaker Feature Store manages historical records of feature data so that features can easily be reproduced at a specific point in time. With Amazon SageMaker Feature Store, you can accelerate machine learning, increase productivity and scale across thousands of models.

To learn more about Amazon SageMaker Feature Store, refer to the documentation. To learn how to use the feature visit the blog post.