Databricks' MLflow Journey: Mastering LLM Evaluation

This article showcases a practical guide to managing and evaluating the performance of Large Language Models (LLMs) using MLflow within the Databricks environment. It's a fantastic resource for anyone looking to streamline their Generative AI experiments and gain insights into their model's accuracy, making it easier to improve model performance. This approach will benefit anyone interested in LLM development.

• •The article provides a step-by-step guide to using MLflow for LLM experiment management.
• •It uses Databricks Free Edition for hands-on experimentation, making it accessible to beginners.
• •The focus is on evaluating LLM answer generation accuracy, a crucial aspect of model performance.