Data quality in Machine Learning and AI hinges on effective data annotation, governed by a crucial Data Annotation Rubric. This rubric outlines objective criteria for label assessment, ensuring model accuracy, consistency, and reduced bias. Mastering the rubric is essential for annotators, impacting both project quality and career advancement in the field.

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