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
Accelerating Vector Search: Using GPU-Powered Indexes with RAPIDS RAFT
freeCodeCamp on LinkedIn: Python GUI Development Using PySide6 and Qt
freeCodeCamp on LinkedIn: How to Level Up Your Developer Portfolio
OpenSearch Service's vector database capabilities explained
Build a simple ChatBOT for your own data using RAG
Jorge Rivera (@acidsnkj) / X
freeCodeCamp on LinkedIn: How to Create a 3D Tilting Card Effect in React Native
Vector Search RAG Tutorial – Combine Your Data with LLMs with Advanced Search
Era of Text Generation: RAG, LangChain, and Vector Databases
freeCodeCamp on LinkedIn: Signals in Angular – How to Write More Reactive Code
Jorge Irsay (@jirsay) / X
Rmz (@remc21) / X
Retrieval-Augmented Generation: How to Use Your Data to Guide LLMs
RAG Using LangChain