SageMaker Unified Studio brings together tools from other AWS services, including the existing SageMaker Studio, to help customers discover, prepare, and process data to build models.

While SageMaker already makes machine learning more accessible, AWS Chief Andy Jassy said SageMaker Studio is a "giant leap forward." ...

“Today, we are announcing a set of tools for Amazon SageMaker that makes it much easier for developers to build end-to-end machine learning pipelines to prepare, build, train, explain, inspect ...

The next generation of SageMaker brings together these capabilities—along with some exciting new features—to give customers all the tools they need for data processing, SQL analytics, ML model ...

AWS upgraded its SageMaker platform to offer more observability and streamlined functions to make AI model inference and training easier.

Popular open source MLflow technology for MLops comes to Amazon SageMaker to help accelerate AI workflows.

At AWS re: Invent, Amazon Web Services, Inc., an Amazon.com, Inc. company, today announced the next generation of Amazon SageMaker, unifying the capabilities customers need for fast SQL analytics ...

Additionally, AWS said that it was adding geospatial capabilities to SageMaker to allow enterprises to increase its use or role in training machine learning models.

AWS's Amazon SageMaker software, a set of tools for deploying machine learning, is not only spreading throughout many companies, it is becoming a key tool for some of the more demanding kinds of ...

Amazon SageMaker adds a data science studio, experiment tracking, production monitoring, and automated machine learning capabilities ...