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Vincent, a machine learning engineer at Explosion, discusses techniques to identify bad labels in training data to ensure trustworthy metrics and model selection. Using the Google emotions dataset with 60,000 texts and 200,000 annotations, he emphasizes the importance of quality input for accurate machine learning outcomes.
