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

AWS says it can speed up training by up to 50%. Next, Amazon SageMaker Inference Recommender automates load testing and optimizes model performance across machine learning instances.

Amazon Web Services (AWS) unveiled a new machine learning service dubbed SageMaker to make the technology available to everyday developers.

AWS is further increasing access to machine learning through Amazon SageMaker Studio Lab, which gives everyone access to a no-cost version of Amazon SageMaker—an AWS service that helps customers ...

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 Web Services (AWS) adds new multi-model engine capabilities to SageMaker as users continue to unlock hidden value in data.

AWS has introduced SageMaker Studio Lab, a free service to help developers learn machine-learning techniques and experiment with the technology. SageMaker Studio Lab provides users with all of the ...

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 ...

At its re:Invent conference, AWS today announced SageMaker Studio Lab, a free service to help developers learn machine learning techniques and experiment with the technology.

· SageMaker Inference Recommender: Automatically suggests the optimal AWS compute instances for running machine learning inference with the best price-performance.

Amazon said SageMaker Studio Lab serves as both a free learning environment for students, and also a free test lab for prototyping new machine learning models.

Amazon SageMaker Canvas provides a visual interface for preparing data and training models, no programming or machine learning expertise required.