At its annual re:Invent conference, AWS today rolled out a slew of new features for SageMaker, the company’s managed service for building, training and deploying machine learning (ML) models.

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.

SageMaker has long been AWS' fully managed platform for building, training, and deploying machine learning and generative AI models. Over time, however, ...

Oct. 26, 2022 — In just 5 years, tens of thousands of customers have tapped Amazon SageMaker to create millions of models, train models with billions of parameters, and generate hundreds of billions ...

At re:Invent 2022, the cloud services provider updated its managed machine learning service to include new notebook and governance features.

Amazon Web Services Inc. expanded its artificial intelligence portfolio at AWS re:Invent today by launching SageMaker Canvas, a tool that enables business users to create machine learning models ...

I spoke with Bratin Saha, VP and General Manager, Machine Learning Services, AWS, about how the cloud has enabled machine learning, and SageMaker’s ability to ease ML deployment.

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