Ensuring High Labeling Quality in Machine Learning Through Consensus-based Labeling
Machine learning (ML) models, the engines driving the artificial intelligence revolution, are only as good as the data they’re trained on. High-quality labeled datasets are foundational for developing accurate and reliable ML models. However, acquiring such datasets is often challenging, especially when it involves subjective judgments or complex scenarios. Consensus-based labeling emerges as a powerful […]
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