SageMaker is AWS's flagship machine learning solution. Here we take a hands-on look at some of its newest features, rolled out in December.

The changes are clearly marked below.] Back in December, when AWS launched its new machine learning IDE, SageMaker Studio, we wrote up a “hot-off-the-presses” review.

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.

At last year’s AWS re:Invent conference, Amazon’s cloud computing unit launched SageMaker HyperPod, a platform for building foundation models.

Amazon Web Services aims to take the “muck” out of machine learning with SageMaker, a new end-to-end machine learning and deep learning stack unveiled today at the AWS re:Invent conference. Machine ...

AWS has added a model for detecting suspicious IP addresses and an implementation of k-means clustering, a method commonly used in AI software to sort images and other files based on similarity.

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.

With SageMaker Model Monitor, AWS customers will be alerted when deviations in the data may be occurring based on a baseline level they configure by feeding a sample of their data to SageMaker.