courseraАнализ данных

Evaluate & Optimize LLM Performance

Курс от Coursera

Средний≈ 4.5 чАнглийский

О курсе

You've integrated a powerful Large Language Model (LLM) into your application. The initial results are impressive, and your team is excited. But then the hard questions start. Is the new prompt really better than the old one, or does it just "feel" better? How do you prove to stakeholders that switching from GPT-3.5 to GPT-4 is worth the extra cost? When you have two models that give slightly different answers, how do you decide which one is objectively superior? After completing this course, you will have the confidence to lead your team in making smart, evidence-based decisions that measurably improve your AI applications. Ready to Become an LLM Expert? It's time to bring scientific rigor to the art of AI. Enroll in Evaluate & Optimize LLM Performance and gain the essential skills to build, validate, and perfect the next generation of language models.

Навыки, которые вы освоите

Test Script Development Statistical Methods Statistical Inference Statistical Analysis Model Evaluation LLM Application Scripting Probability & Statistics Prompt Engineering Data-Driven Decision-Making Large Language Modeling Statistical Hypothesis Testing Embeddings Natural Language Processing Model Optimization Performance Metric

Программа курса

3 модулей · 19 учебных материалов

01Build Automated LLM Evaluation Systems6 материалов

Welcome: Why Does "Good" AI Content Go Bad?DIALOGUE A Guide to LLM Evaluation: Lexical and Semantic MetricsЧтение How to Compute Lexical Metrics: BLEU & ROUGE-L in Python?Видео How to Compute Semantic Similarity with Embeddings?Видео

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