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Episode 32: Building Reliable and Robust ML/AI Pipelines

Vanishing Gradients

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Enhancing LLM Data Quality with SPaDE

This chapter explores the SPaDE framework, aimed at synthesizing data quality assertions for LLM pipelines while addressing common pitfalls in custom data processing workflows. It emphasizes the importance of user feedback and innovative metrics in improving machine learning evaluation and the effective roles of human evaluators and LLMs in the validation process.

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