Production data labeling workflows
Practical AI
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Enhancing Data Labeling Workflows
This chapter explores the challenges organizations face with crowdsourced data labeling, emphasizing the negative impact of poor instructions and varied annotator motivations. It advocates for a tailored approach with trained teams to improve data quality and discusses the complexities of integrating efficient workflows and automation tools. Key strategies for effective communication, project management, and the importance of a robust training system for annotators are highlighted to enhance the accuracy and efficiency of labeling projects.
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