Vector Search

Vector search is a type of search algorithm and technique for finding similar items or nearest neighbors in high-dimensional vector spaces based on their similarity or distance metrics. It is widely used in information retrieval, recommendation systems, and machine learning applications for searching and matching items, such as documents, images, and embeddings, using vector representations and similarity measures. Readers can explore vector search algorithms, data structures, and applications, such as cosine similarity, Euclidean distance, and nearest neighbor search, understanding their efficiency and effectiveness in similarity search and recommendation tasks.

Comprehensive roadmap for vector-search

By roadmap.sh