Retrieval Augmented Generation (RAG) Explained for Beginners | Boost Your LLMs 🚀

In this video, we'll explain LLMs and RAG, covering key components like retrieval and generation. Further, we'll demonstrate the RAG workflow in practice. and understand practical applications and challenges like hallucinations. We will dive into a hands-on with RAG implementation using LangChain. From importing libraries to detailed demonstrations, this video covers it all. Watch now to gain essential knowledge and hands-on experience!

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🏁 Topics Covered:
00:00:00 Introduction
00:01:04 Introduction to LLMs
00:11:57 Limitations of LLMs
00:14:04 Introduction to RAG
00:20:24 RAG Basics Concepts and Terminology
00:32:36 Key Components - Retrieval and Generation
00:41:00 Workflow of RAG
00:52:25 Applications of RAG
01:06:59 Hallucinations in RAG
01:15:40 Steps to implement RAG with LangChain
01:24:30 Hands-on RAG - Importing Libraries
01:36:06 Hands-on RAG in detail
01:41:33 RAG - Summary

#rag #llm #retrievalaugmentedgeneration #ml

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