Web Reference: Learn how vector databases power semantic search, embeddings, and RAG. Explore HNSW indexing, hybrid search, and performance metrics for modern AI applications. Aug 2, 2025 · This book delivers a technical blueprint for professionals and teams who want to harness the full potential of vector databases to accelerate retrieval-augmented generation (RAG), improve semantic search, and streamline end-to-end machine learning workflows. Understanding every little detail on vector databases and their utility in LLMs, along with a hands-on demo.
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