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general:products/amazon-sagemaker,general:products/amazon-machine-learning

SageMaker Region expansion to Bahrain

Source: AWS Amazon SageMaker is now available in Middle East (Bahrain) Region.  

Amazon SageMaker Notebooks now export Jupyter logs to Amazon Cloudwatch

Source: AWS You can now view your Amazon SageMaker Notebook logs in Amazon Cloudwatch. Notebook logs provide key details such as events, metrics, and health information, which can be used to generate actionable insights about your SageMaker notebooks. 

Amazon SageMaker notebooks now available with pre-installed R kernel

Source: AWS Amazon SageMaker notebooks now support R out-of-the-box, without needing you to manually install R kernels on the instances. Also, the notebooks come pre-installed with the reticulate library that offers an R interface for the Amazon SageMaker Python SDK enabling you to invoke Python modules from within an R script.  

New Model Tracking Capabilities for Amazon SageMaker Are Now Generally Available

Source: AWS New model tracking capabilities for Amazon SageMaker are now generally available in all AWS regions where Amazon SageMaker is available. With these new capabilities, you can quickly and easily find and compare your machine learning (ML) model training experiments. Using either the AWS Management Console or the AWS SDK, you can quickly search through thousands of model training experiments and compare metrics to evaluate performance across different iterations, accelerating your ability to identify the best performing models.