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You want to label images so you can create a dataset for training your machine learning models. Can you do this by setting up a labeling job in SageMaker Ground Truth? -- SageMaker is a fully managed service to prepare data and build, train, and deploy machine learning (ML) models for any use case with fully managed infrastructure, tools, and workflows. -- Tutorial Summary: Start by choosing an image for a task category in AWS Sagemaker Groundtruth Label Job. Set up a labeling job for creating a dataset for machine learning models. Navigate to the S3 service and upload images (six images of cats and dogs) to a test bucket. In Amazon SageMaker service, go to Ground Truth and create a labeling job. Name the job, select automated data setup, and choose the S3 test bucket. Create a new IAM role with access to the test bucket and complete data setup. Confirm the presence of a manifest file in the test bucket. Select the task category as single label image classification. Choose private for worker types and enter worker email addresses. Leave timeout and expiration time as default. Enter an organization and support email. Provide a brief description of the task and enter two labels (one for cat and one for dog). Preview the setup and create the job. Verify that the labeling job is in progress. Log into the labeling project, complete the labeling, and check for any remaining images. Once the labeling job is complete, go to the output section to view the labeled images.