For example, you can send labeling jobs to your own labelers, or you can access a workforce of over 500,000 independent contractors who are already performing ML-related tasks through Amazon Mechanical Turk.
You have options to work with labelers inside and outside your organization. Second, with SageMaker Ground Truth, you can build and manage your data labeling workflows. First, with SageMaker Ground Truth Plus, an expert workforce that is trained on ML tasks labels your data in accordance with your quality and turnaround time requirements. With Amazon SageMaker data labeling offerings, you have two options to label data. SageMaker Ground Truth can generate hundreds of thousands of automatically labeled synthetic images on your behalf. You can also generate labeled synthetic data without manually collecting or labeling real-world data. SageMaker Ground Truth is a data labeling service that makes it easy to label data and gives you the option to use human annotators through Amazon Mechanical Turk, third-party vendors, or your own private workforce. If you want the flexibility to build and manage your own data labeling workflows and workforce, you can use SageMaker Ground Truth.
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You upload your data, and then SageMaker Ground Truth Plus creates and manages data labeling workflows and the workforce on your behalf. SageMaker Ground Truth Plus provides an expert workforce that is trained on ML tasks and can help meet your data security, privacy, and compliance requirements. SageMaker Ground Truth Plus helps reduce data labeling costs by up to 40%. SageMaker offers two options, Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth, which provide you with the flexibility to use an expert workforce to create and manage data labeling workflows on your behalf or manage your own data labeling workflows.Īmazon SageMaker Ground Truth Plus With SageMaker Ground Truth Plus, you can create high-quality training datasets without having to build labeling applications or manage labeling workforces on your own. Amazon SageMaker enables you to identify raw data, such as images, text files, and videos add informative labels and generate labeled synthetic data to create high-quality training datasets for your machine learning (ML) models.
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