Embeddings and Vector Search

In this lesson, we will learn embeddings and vector search. We will explain how text is converted into vectors, semantic search, similarity, vector databases, cosine similarity and how embeddings are used in AI systems with practical examples. ## Lesson objective In this lesson, we will learn embeddings and vector search. In the previous lesson, we covered content, research and automation workflows with AI. We explained how to use AI for email, reports, blog outlines, meeting summaries, task extraction, document summaries and automation workflows.