Synthetic Data Generation
Sahil discusses the importance of defining data expectations clearly to reduce ambiguity in synthetic data generation. By allowing users to transform sample data, they can create complex datasets tailored to their needs, enhancing model training quality. The platform also emphasizes user feedback, enabling continuous improvement of models based on real-world performance insights.In this clip
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