Vector Databases | A Practical Crash Course in 1 hour

This video provides a practical crash course to Vector Databases. We cover the basics of a Vector, then move on to what vector embeddings are. Next we explore how vector embeddings capture context in unstructured data. We explain how semantic search works. This lead us to the nearest neighbours and approximate nearest neighbours techniques for vector indexing.

In the last part of the video we explore a practical example of how to use a vector db with a semantic search application using Pinecone.

The instructor is Dr Anil Variyar who has a PhD in Aeronautics and Astronautics from Stanford University.

00:00 - What is a Vector Database
00:02 - What is Vector?
00:08 - What are Vector Embeddings?
00:15 - Vector Similarity
00:23 - Approximate Nearest Neighbours
00:38 - Building a Pinecone Adapter in Python

#generativeai #genai #semanticsearch #pinecone #deeplearning #machinelearning #python