Data Labeling Challenges
Mark discusses the challenges of using a crowdsourced approach for data labeling, highlighting the issues of unclear instructions and varying motivations of labelers. He emphasizes the need for a more bespoke approach with handpicked and highly trained teams to ensure a clean and accurate dataset. Daniel shares his own experience with data quality struggles in speech projects and the expensive solution of requiring multiple labels for each sample.In this clip
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Practical AI
Production data labeling workflows
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