30 Days of LLMs: Day 24 - LLM Result Analysis Explained
For Day 24 of the W&B 30 Days of LLMs, we dive into analyzing LLM evaluation results. Discover how to use the W&B dashboard for error identification and iterative improvements.
Created on December 18|Last edited on December 22
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We'll be taking a day-by-day look at our Building LLM-Powered Applications course — and giving you the chance to win some great prizes!
30 Days of LLMs Contest
By enrolling in our free Building LLM-Powered Applications course, you will automatically be entered into a prize draw to win the coveted W&B socks. Complete the course, and you'll be entered into the draw to win a pair of Apple AirPods Pro!
Day 24 - LLM Result Analysis Explained
Welcome to Day 24 of our complimentary course, "Building LLM-Powered Apps". In this segment, Darek Kleczek, a Machine Learning Engineer at W&B, guides you through interpreting evaluation data for LLM projects. Acquire skills in using the Weights & Biases interface to detect and correct errors in your LLM tools.
Chapter Highlights
- In-depth Analysis of Evaluation Data: Understand how to scrutinize assessment data using the Weights & Biases platform.
- Interactive Data Examination Techniques: Find out how to employ filters and interactive elements to identify weak points in the model's performance.
- Spotting Errors and Gaining Insights: Learn the methods for pinpointing specific mistakes and deriving insights for potential enhancements in your LLM tools.
- The Cycle of Continuous Enhancement: Master the ongoing process of analysis, corrections, and reassessment to boost the efficacy of LLM tools.
Key Course Information
- No deep machine learning knowledge is needed, just some familiarity with Python programming.
- Strategies for continual enhancement of your LLM applications.
- Unique perspectives on the LLM tools used by Weights & Biases.
Free Enrollment
Preview of the Next Chapter
Join us for tomorrow's installment where we will recap the course and discuss the future steps in evolving LLM tool development
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