DOMAIN 6 · Intermediate
Embeddings & Vector Search
Understand how we turn text into meaning-aware numbers, and build search that finds what the user meant — not just the words they typed.
Audience: A developer comfortable with LLMs who wants to build real semantic search or RAG — not just a notebook demo.
CONCEPTS IN ORDER1What Is an EmbeddingT1 · 7 min2Measuring Vector SimilarityT1 · 7 min3Semantic Search — Searching by Meaning, Not WordsT1 · 8 min4Chunking — Splitting Your DocumentsT1 · 7 min5Vector DatabasesT1 · 8 min6Embedding Models — Picking the Right OneT1 · 7 min7Retrieval Quality — Measuring What You Get BackT1 · 8 min