Evaluating RAG Solutions
Evaluating RAG Solutions
Duration: 17m 15s | .MP4 1920x1080, 30 fps(r) | AAC, 48000 Hz, 2ch | 54.36 MB
Genre: eLearning | Language: English
Duration: 17m 15s | .MP4 1920x1080, 30 fps(r) | AAC, 48000 Hz, 2ch | 54.36 MB
Genre: eLearning | Language: English
Retrieval-Augmented Generation (RAG) enhances LLMs by accessing external knowledge, but requires proper evaluation. This course will teach you how to assess RAG systems using comprehensive evaluation methodologies and metrics.
What you'll learn
Implementing Retrieval-Augmented Generation (RAG) systems without proper evaluation methods can lead to unreliable outputs and missed optimization opportunities. In this course, Evaluating RAG Solutions, you will learn essential techniques to thoroughly assess and improve RAG implementations through hands-on demos using Python and RAGAS. First, you will explore fundamental evaluation metrics for both retrieval and generation components. Next, you will discover practical evaluation frameworks and tools to systematically measure RAG performance. Finally, you will learn how to interpret evaluation results and implement targeted improvements. When you are finished with this course, you will have the skills and knowledge of RAG evaluation needed to build more accurate, reliable, and efficient RAG solutions.
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