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Data collection and labeling: Machine Learning course | Zoonk

11. Data collection and labeling

Plan collection, labeling, sampling, consent, documentation, retention, and access. Recognize proxy variables, historical bias, label ambiguity, leakage risks, and populations missing from the dataset.

Machine Learning

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