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Related Questions
- What are the common challenges faced by data curators when annotating data for machine learning models?
- How does human bias affect the accuracy of machine learning models, and what role does data curation play in mitigating this issue?
- What are some strategies for ensuring the quality and consistency of annotated data in machine learning model development?
- Can you explain the concept of active learning and its potential applications in data curation and annotation for machine learning models?
- How does the cost and time required for data curation and annotation impact the development and deployment of machine learning models?
- What are some potential solutions for automating or streamlining the data curation and annotation process for machine learning models?
- Can you discuss the importance of data provenance and auditability in machine learning model development, and how data curation can help address these concerns?
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