Recall@K Explained | Evaluate Your RAG Pipeline & AI Retrieval System #langgraph #langchain #aiagent

Description

No matter how advanced your **RAG pipeline** or AI agent system is, the real question is: Did the system retrieve the right information? To answer this, we rely on **evaluation metrics** — and in this video, we break down one of the most important ones: Recall@K What is Recall@K? Recall@K measures how many relevant documents your system successfully retrieves out of all the relevant documents available. Why Recall@K matters: 1. Helps evaluate retrieval quality in **RAG systems** 2. Measures how well your system finds useful information 3. Critical for improving **AI search and agent performance** By understanding Recall@K, you can **analyze, debug, and improve** your AI system’s accuracy and effectiveness. #rag #recallatk #ai #machinelearning #artificialintelligence #generativeai #llm #aieval #datascience #python #coding #developers #aiagents #search #informationretrieval #mlmetrics #softwareengineering #tech #programming #aitutorial #learningai