AWS expands its widely adopted machine learning service, combining comprehensive data, analytics, and AI capabilities LAS VEGAS--(BUSINESS WIRE)-- At AWS re:Invent, Amazon Web Services, Inc. (AWS ...

SageMaker will get streaming algorithms and better batch processing and pluck data directly from Amazon's S3 storage.

For instance, customers can integrate Amazon Aurora MySQL, PostgreSQL and other kinds of databases directly with Amazon SageMaker, without needing to build any complex data pipelines first.

AWS has announced the 'next generation' of its SageMaker AI dev platform, including a unified data dashboard.

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

Remote training is exactly the same thing - except the data is transferred from S3 into the standard folder on disk, and the whole workflow executes on SageMaker: ...

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 ...

The new SageMaker Unified Studio makes it easy for customers to find and access data from across their organization and brings together purpose-built AWS analytics, machine learning (ML), and AI ...