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Building reliable datasets requires thoughtful selection to ensure variety, fairness, and precise labeling.
Different tasks require tailored dataset structures and labeling schemes. For image recognition tasks, datasets should include accurately annotated images and balanced class distributions.
Ethical and legal considerations shape dataset creation and sharing policies. Establishing clear consent, transparency, and oversight mechanisms is key to responsible data management.
Evaluation datasets and benchmarks enable objective comparison of models. Maintaining datasets over time helps adapt to distribution shifts and new contexts.
Ongoing updates to datasets are needed to track changing domains and emerging patterns. |