A Beginner’s Guide to Vector Databases and Semantic Search
freeCodeCamp News
EDITOR BRIEF
A freeCodeCamp course introduces vector databases, which use numerical representations of data called embeddings to search by meaning. It covers similarity measures, tokenization, embeddings with Gemini, database indexing, and a hands-on semantic search project using ChromaDB.
INSIGHTS
Understanding vector search is useful for building recommendation systems and retrieval-augmented generation (RAG) apps. A practical next step is to follow the course and build the ChromaDB semantic search project.
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