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AWS sagemaker documentation change

Service: sagemaker · 2025-11-19 · Documentation low

File: sagemaker/latest/dg/sms-automated-labeling.md

Summary

Updated terminology from 'AWS CloudFormation stack' to 'CloudFormation stack' in automated labeling documentation

Security assessment

Change is purely terminological (removing 'AWS' prefix from CloudFormation). No security context, vulnerability fixes, or security features are mentioned or implied in the change.

Diff

diff --git a/sagemaker/latest/dg/sms-automated-labeling.md b/sagemaker/latest/dg/sms-automated-labeling.md
index bdee64e11..cd0ea0a30 100644
--- a//sagemaker/latest/dg/sms-automated-labeling.md
+++ b//sagemaker/latest/dg/sms-automated-labeling.md
@@ -162 +162 @@ Ground Truth manages the instances that you use for automated data labeling jobs
-You can create an active learning workflow with your own algorithm to run training and inferences in that workflow to auto-label your data. The notebook bring_your_own_model_for_sagemaker_labeling_workflows_with_active_learning.ipynb demonstrates this using the SageMaker AI built-in algorithm, [BlazingText](https://docs.aws.amazon.com/sagemaker/latest/dg/blazingtext.html). This notebook provides an AWS CloudFormation stack that you can use to execute this workflow using AWS Step Functions. You can find the notebook and supporting files in this [GitHub repository](https://github.com/awslabs/amazon-sagemaker-examples/tree/master/ground_truth_labeling_jobs/bring_your_own_model_for_sagemaker_labeling_workflows_with_active_learning).
+You can create an active learning workflow with your own algorithm to run training and inferences in that workflow to auto-label your data. The notebook bring_your_own_model_for_sagemaker_labeling_workflows_with_active_learning.ipynb demonstrates this using the SageMaker AI built-in algorithm, [BlazingText](https://docs.aws.amazon.com/sagemaker/latest/dg/blazingtext.html). This notebook provides an CloudFormation stack that you can use to execute this workflow using AWS Step Functions. You can find the notebook and supporting files in this [GitHub repository](https://github.com/awslabs/amazon-sagemaker-examples/tree/master/ground_truth_labeling_jobs/bring_your_own_model_for_sagemaker_labeling_workflows_with_active_learning).