3 Vector-based Methods for Similarity Search (TF-IDF, BM25, SBERT)

Vector similarity search is one of the fastest-growing domains in AI and machine learning. At its core, it is the process of matching relevant pieces of information together. Similarity search is a complex topic and there are countless techniques for building effective search engines. In this video, we’ll cover three vector-based approaches for comparing languages and identifying similar ’documents’, covering both vector similarity search and semantic search: - TF-IDF - BM25 - Sentence-BERT 📰 Original article: 🤖 70% Discount on the NLP With Transformers in Python course: 🎉 Sign-up For New Articles Every Week on Medium! @jamescalam/membership Mining Massive Datasets Book (Similarity Search): 📚 (3rd ed) 📚 (1st ed, cheaper) 👾 Discord 🕹️ Free AI-Powered Code Refactoring with Sourcery: