Launched at AWS re:Invent 2021, Amazon SageMaker Ground Truth Plus helps you create high-quality training datasets by removing the undifferentiated heavy lifting associated with building data labeling applications and managing the labeling workforce. All you do is share data along with labeling requirements, and Ground Truth Plus sets up and manages your data labeling workflow based on these requirements. From there, an expert workforce that is trained on a variety of machine learning (ML) tasks performs data labeling. You don’t even need deep ML expertise or knowledge of workflow design and quality management to use Ground Truth Plus.
Building a high-quality training dataset for your ML algorithm is an iterative process. ML practitioners often build custom systems to inspect data labels because accurately labeled data is critical to ML model quality. To ensure you get high-quality training data, Ground Truth Plus provides you with a built-in user interface (Review UI)

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