Understanding Ground Truth in AI/ML: Implementation, Use Cases, and AWS Services

Understanding Ground Truth in AI/ML: Implementation, Use Cases, and AWS Services

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Ground truth is a fundamental concept in Artificial Intelligence (AI) and Machine Learning (ML). It refers to the accurate, real-world data used to train, validate, and test models. The effectiveness of an AI model largely depends on the quality of the ground truth data, making it essential for achieving high accuracy and reliability.

In this video, we’ll explore what ground truth means in AI/ML, how to implement it, its applications, and how AWS services facilitate ground truth data management.