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Related Questions
- What are some common sources of bias in large datasets used for machine learning?
- How can data curation and preprocessing impact the fairness of machine learning models?
- Can you explain the concept of representativeness and its relation to bias in large datasets?
- What are some methods to detect and mitigate bias in machine learning models?
- How does the concept of 'garbage in, garbage out' relate to bias in machine learning?
- Can you provide examples of real-world scenarios where biased data led to flawed machine learning models?
- What role do annotation and labeling play in introducing bias into machine learning datasets?
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