Getting started

Amazon SageMaker provides two data labeling offerings, Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth. Both options allow you to identify raw data, such as images, text files, and videos, and add informative labels to create high-quality training datasets for your machine learning models. Get started with these developer resources.

Introduction to Amazon SageMaker Ground Truth Plus

Create high-quality training datasets without having to build labeling applications or manage a labeling workforce.

DEVELOPER GUIDE


Follow this step-by-step guide to start using Amazon SageMaker Ground Truth Plus. 

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Read this blog to understand how to create training datasets without In-house resources and save cost. 

TUTORIAL


In this video, watch AWS experts share how you can easily create high-quality training datasets without having to build labeling applications and manage your own labeling workforce.

AWS re:Invent 2021 - AWS On Air ft. Amazon SageMaker Ground Truth Plus (20:52)

Introduction to Amazon SageMaker Ground Truth

Learn how to build highly accurate training datasets.

DEVELOPER GUIDE


Follow this step-by-step guide to start using Amazon SageMaker Ground Truth quickly. 

TUTORIAL


Get started with labeling training datasets in 10 minutes.

WEBINAR


In this on-demand tech talk, learn to label training data using workflows in Amazon SageMaker Ground Truth.

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Read this blog to understand how to save money on data labeling.

Label data accurately and quickly

Use these resources to label data for training data sets in the shortest time.

VIDEO


In this video, watch an AWS expert label data and create highly accurate training datasets.

Build Highly Accurate Training Datasets at Reduced Costs with Amazon SageMaker Ground Truth (13:58)

WEBINAR


In this on-demand tech-talk, learn how data labeling can help customer support representatives more efficiently manage help requests.

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Learn how to use a trained model from a previous labeling job to jump-start a new job with Amazon SageMaker Ground Truth.

HANDS-ON LAB


Follow these exercises on GitHub to use Amazon SageMaker Ground Truth.

VIDEO


Learn how the National Football League (NFL) uses Amazon SageMaker Ground Truth to build training datasets to track players moving on the field. You will learn to setup video labeling jobs, monitor labels, and identify problematic labels in this interactive video.

How the National Football League (NFL) builds computer vision training datasets at scale

Custom workflows

Bring custom data labeling workflows to Amazon SageMaker Ground Truth.

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In this blog, learn how to use a custom workflow in Amazon SageMaker Ground Truth.

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Learn to create pre and post-processing datasets for custom workflows.

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Learn how automated data labeling significantly reduces data labeling costs.

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Learn more about Amazon SageMaker data labeling features

Visit the features pages
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