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L-7 RAG (Retrieval Augmented Generation)
Generative AI Tutorials
In this video, we dive into the fascinating world of RAG, or Retrieval-Augmented Generation. GitHub: https://github.com/AarohiSingla/Generative_AI/tree/main/L-7/RAG_demo Email: [email protected] We'll explore what RAG is, why it’s an essential tool in the realm of artificial intelligence, and how it functions. Starting with the theory behind RAG, we'll break down its components and explain its significance in enhancing the capabilities of generative models. Then, we'll move on to a practical demonstration, showing you how to implement RAG in real-world scenarios. Whether you're a beginner looking to understand the basics or an enthusiast seeking to deepen your knowledge, this video provides a comprehensive overview of Retrieval-Augmented Generation and its applications.
About the course
Welcome to our Generative AI playlist! This curated collection of videos explores the exciting and rapidly evolving field of Generative Artificial Intelligence. Throughout this playlist, you'll find comprehensive guides on various large language models (LLMs), including their capabilities, applications, and how to utilize them effectively. We'll also dive deep into LangChain, a powerful tool for building generative AI applications. Whether you're a beginner looking to understand the basics or an experienced developer seeking advanced insights, this playlist has something for everyone. Join us as we uncover the potential of Generative AI and learn how to leverage it for innovative solutions!
20lessons
3hours
Lessons
- L-1 Generative AI for Beginners
- L-1 Generative AI for Beginners
- L 2 Ollama | Run LLMs locally
- L 2 Ollama | Run LLMs locally
- L-3 LangChain Explained | Building Generative AI Apps from Scratch
- L-3 LangChain Explained | Building Generative AI Apps from Scratch
- L-4 Step-by-Step Guide to Building a ChatGPT Clone
- L-4 Step-by-Step Guide to Building a ChatGPT Clone
- L-5 Chat with database using LangChain
- L-5 Chat with database using LangChain
- Run Llama 3.1 locally using LangChain
- Run Llama 3.1 locally using LangChain
- L-7 RAG (Retrieval Augmented Generation)
- L-7 RAG (Retrieval Augmented Generation)
- L-8 Build a Q&A App with RAG using Gemini Pro and Langchain
- L-8 Build a Q&A App with RAG using Gemini Pro and Langchain
- L-9 Build a Q&A App with RAG, LangChain, and Open-Source LLMs | Step-by-Step Guide
- L-9 Build a Q&A App with RAG, LangChain, and Open-Source LLMs | Step-by-Step Guide
- L-10 RAG Vs Fine-tuning
- L-10 RAG Vs Fine-tuning