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Related Questions
- What are the key differences between active learning and human-in-the-loop approaches in machine learning?
- How can active learning strategies such as uncertainty sampling and query-by-committee help reduce annotation bias?
- What are some common pitfalls to avoid when implementing human-in-the-loop approaches to mitigate annotation bias?
- Can you provide examples of successful applications of active learning and human-in-the-loop approaches in real-world machine learning projects?
- How can data scientists and machine learning engineers work together to design effective human-in-the-loop workflows that reduce annotation bias?
- What role does domain knowledge play in reducing annotation bias in machine learning, and how can it be incorporated into active learning and human-in-the-loop approaches?
- What are some emerging techniques in active learning and human-in-the-loop approaches that show promise in reducing annotation bias, such as transfer learning and multi-task learning?
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