13 Oct RAG Tutorial

Retrieval Augmented Generation (RAG) as an approach to enhance the output of LLMs. You would be wondering, how? Well, because RAG provides LLMs with relevant, and fresh data and documents. The data is real-time and context-specific. RAG includes both retrieval and generation.

Viewers

The Retrieval Augmented Generation (RAG) tutorial is prepared for students, engineers, and professionals. It will help them understand RAG concepts.

RAG Tutorial – Index

☑️ RAG – Introduction

• What is RAG (Retrieval Augmented Generation)

☑️ RAG – Comparisons

• How RAG is better than traditional retrieval models
• How RAG is better than standalone generative models

☑️ RAG – Process

• Approaches/ Techniques of RAG
• Process of RAG
• Example of RAG

☑️ More about RAG

• Vector Embeddings in RAG and its process
• Applications of RAG
• Advantages of RAG
• Disadvantages of RAG

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