Episode 21: Deploying LLMs in Production: Lessons Learned
Vanishing Gradients
00:00
Importance of Looking at and Cleaning Data
The speakers emphasize the significance of data cleaning and analysis in the field of data science, highlighting tasks like handling delimiter issues, debugging, and engineering purposes. They discuss the need for custom applications to analyze messy data generated by language models and multi-turn conversations. The chapter explores the skills required for working with language models and generative AI, emphasizing the importance of skepticism, metric design, and rigorous evaluation.
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