Vector Search and RAG Tutorial – Using LLMs with Your Data

You can use Vector Search and embeddings to easily combine your data with large language models like GPT-4. I just published a course on the channel that will teach you how to implement Vector Search on three different projects. First, you will learn about the concepts and then
You can use Vector Search and embeddings to easily combine your data with large language models like GPT-4. I just published a course on the channel that will teach you how to implement Vector Search on three different projects. First, you will learn about the concepts and then I'll guide you through developing three projects. In the first project we build a semantic search feature to find movies using natural language queries. For this we use Python, machine learning

Guide to Building a RAG Based LLM Application

All You Need to Know about Vector Databases and How to Use Them to Augment Your LLM Apps, by Dominik Polzer

Introduction To Retrieval Augmented Generation - Arize AI

freeCodeCamp on LinkedIn: How to Sort a List Recursively in Python

Gartner RAG Tips for Grounding LLMs with Relevant Internal Data

Jorge Rivera (@acidsnkj) / X

Improving Large Language Models with Retrieval Augmented Generation