Transform data into ML features using SageMaker Feature Store feature processing
Amazon SageMaker Feature Store now supports feature processing, a new capability that enables you to transform data into ML features. With this launch, you simply provide a data source, and the transformation function you want to perform on the data and SageMaker Feature Store takes care of processing the data into ML features.
Amazon SageMaker Feature Store now supports feature processing, a new capability that enables you to transform data into ML features. With this launch, you simply provide a data source, and the transformation function you want to perform on the data and SageMaker Feature Store takes care of processing the data into ML features.
With the new launch, SageMaker Feature Store can pull the data from your batch data sources or existing feature groups, apply the transformation code, and ingest data to a Feature Group specified by you. It manages the processing of feature transforms as well as creates and maintains feature pipelines in the background. It also enables monitoring of the pipelines, and lineage tracking thereby making it easier for teams to productionize their feature pipelines for ML applications. You can track your scheduled pipeline executions, visualize lineage to trace features back to their data sources, and view shared feature processing code all in one environment in Amazon SageMaker Studio.
To learn more, please view the documentation here. To get started, go to SageMaker Studio from the Amazon SageMaker console.