Amazon SageMaker Runtime

2020/12/08 - 1 updated api methods

Changes   This feature helps you monitor model performance characteristics such as accuracy, identify undesired bias in your ML models, and explain model decisions better with explainability drift detection.

2020/06/05 - 1 updated api methods

Changes   You can now specify the production variant to send the inference request to, when invoking a SageMaker Endpoint that is running two or more variants.

2019/11/18 - 1 updated api methods

Changes   Amazon SageMaker now supports multi-model endpoints to host multiple models on an endpoint using a single inference container.

2018/08/29 - 1 updated api methods

Changes   SageMaker Runtime supports CustomAttributes header which allows customers provide additional information in a request for an inference submitted to a model or in the response about the inference returned by a model hosted at an Amazon SageMaker endpoint.

2017/11/29 - 1 new api methods

Changes   Amazon SageMaker is a fully-managed service that enables data scientists and developers to quickly and easily build, train, and deploy machine learning models, at scale.