📄️ 📘 Lecture notes
There are several ways to tune and optimize your vector search queries. In this lab, we will focus on the following:
📄️ 👐 Pre-filtering
Pre-filtering is a technique to optimize vector search by only considering documents that match certain criteria during vector search.
📄️ 👐 Changing the similarity metric
The similarity metric determines how nearest neighbors are calculated, and consequently what items are retrieved during vector search.
📄️ 🦹♀️ Vector quantization
Vector quantization is a technique to reduce the number of bits required to represent a vector. This can help reduce the storage and memory requirements for vector embeddings.