How do you evaluate an LLM? Try an LLM.

Explore the challenges of evaluating Large Language Models (LLMs) in data science, emphasizing validation against a 'source of truth'. Discover techniques for improving evaluation, including custom benchmarks and prompt engineering. Delve into the risks of LLM self-evaluation and the importance of diverse synthetic data. Dive into the factors influencing model deployment decisions and maintenance considerations.