SageMaker Studio makes model building, monitoring easier

AWS launched a host of new tools and capabilities for Amazon SageMaker, AWS' cloud platform for creating and deploying machine learning models; drawing the most notice was Amazon SageMaker Studio, a web-based integrated development platform (IDE) . In addition to SageMaker Studio, the IDE for platform for building, using, and monitoring machine learning models, the other new AWS products aim to make it easier for non-expert developers to create models and to make them more explainable. During a keynote presentation at the AWS re:Invent 2019 conference here Tuesday, AWS CEO Andy Jassy described five other new SageMaker tools: Experiments, Model Monitor, Autopilot, Notebooks, and Debugger. "SageMaker Studio along with SageMaker Experiments, SageMaker Model Monitor, SageMaker Autopilot, and Sagemaker Debugger collectively add lots more lifecycle capabilities for the full ML (machine learning) lifecycle and to support teams," said Mike Gualtieri, an analyst at Forrester. SageMaker Studio, Jassy claimed, is a "fully-integrated development environment for machine learning." The new platform pulls together all of SageMaker's capabilities, along with code, notebooks, and datasets, into one environment.