Search is a fundamental problem in computing, and vector search aims to match meanings rather than exact words. By converting queries and documents into numerical vectors and calculating similarity, vector search retrieves contextually relevant results. In this tutorial, a vector search system is built from scratch in Python using a toy dataset and word embeddings, showcasing the core principles behind how vector search works.
