GitHub: https://github.com/knodax-labs-demo/aws-data-and-ml-labs/blob/main/15-exploring-image-labeling-with-mechanical-turk-ground-truth.md
Learn how to set up your first Amazon SageMaker Ground Truth labeling job in this beginner-friendly, step-by-step hands-on tutorial.
In this video, you will:
Create and configure a SageMaker Domain
Explore Ground Truth, including Labeling Jobs, Labeling Domains, and Labeling Workforces
Upload images to Amazon S3 for labeling
Configure input and output datasets
Create IAM roles for secure access
Review labeling task types and worker options
Understand how Ground Truth manages labeling workflows
This walkthrough is perfect for:
✔ Data scientists
✔ Machine learning beginners
✔ AI practitioners
✔ Anyone learning SageMaker or preparing for AWS certifications
⚠️ Important Note About Costs
Amazon SageMaker and Ground Truth are not free. Charges may occur for domain setup, labeling jobs, S3 storage, and compute usage. If you want to avoid costs, feel free to watch the tutorial without running the steps in your own AWS account.
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