Module 2

Further Reading

• Distance Metrics A closer look at cosine similarity, dot product, Euclidean, and Manhattan, and when each one fits.
• What Is HNSW How the graph index is built and tuned, once you have real searches to measure it against.
• Filtering The full filter syntax, including range, geo, and nested conditions.
• Payload Indexing The available payload index types and how to configure them.
• Chunking Strategies The full comparison of fixed-size, semantic, and sliding-window chunking, with worked examples.

What’s Next: Module 3

Dense vectors capture meaning well, but they can miss exact keyword matches such as product codes or model numbers. Module 3 introduces sparse vectors, which complement dense vectors by capturing exact terms and keywords. You’ll learn how to combine both in a single hybrid search query.