Unlike traditional machine learning datasets with isolated examples, conversational AI datasets must capture the dynamic flow of human dialogue. They need to preserve context across multiple turns, handle shifting meanings, and represent the full spectrum of human communication styles.

This comprehensive guide explores the essential components of building robust conversational AI datasets—from data collection strategies to quality assurance and deployment considerations.

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