Creating, storing and retrieving vector data
Course Content
0 / 38 completedExplain vector database like I'm 5
Vectors and Embeddings
How vector database store data
Introduction to Vector Database
How do vector database works
Vectors in 2D
Create embeddings using OpenAI
Finding nearest vector
Setup and basic operations
Creating, storing and retrieving vector data
Vector search using sqlite-vss extension
Methods on collections
Introduction to ChromaDB
Storing The Matrix collections
Adding document associated embeddings
Query data with 'where' filter
ChromaDB + Langchain - QA on multiple documents - Part 2
ChromaDB + Langchain - QA on multiple documents - Part 1
Using similarity search for nearest neighbours
Introduction to FAISS
Setup account, create an index, dashboard review
Introduction to Pinecone
Index management
Understanding index creation configuration
Upsert batches in parallel
Query vector data
Upsert vector data in batches
Insert vector data to an index
Vector IDs must be string
Sentence transformer embeddings
Semantic search with metadata filtering - news articles
Introduction to Qdrant vector database
Connect with APIs
Create a qdrant python client
Create a collection
Create a vector store
Add document to vector store on the cloud
Query the document