Module 2
Vector indexes
In this module, you will learn how to work with vector Full definition for embedding (opens in a new tab)Information represented as a numerical vector, positioned so that similar information sits close together. and vector indexes in Neo4j. Vector indexes allow you to perform fast similarity search across millions of Full definition for node (opens in a new tab)A vertex in a graph. In a property graph it can carry labels and properties. using cosine or Euclidean similarity.
In this module, you will learn:
- What embeddings are and how to load them into Neo4j
- How to create and query vector indexes in Neo4j
- The different similarity functions available in Neo4j
You will use a dataset of questions and answers to practice creating and querying vector indexes.
If you are ready, let's get going!