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Vector Database Mastery: Foundations, Indexing, and Semantic Search with FAISS, Milvus, and Pinecone
Paperback
Series: Vector Database Mastery: From Foundations to Production-Ready AI Search Systems, Book 1
Publisher: Independently Published
Published: Dec 8 2025
Pages: 162
Weight: 0.64
Height: 0.35 Width: 7.00 Depth: 10.00
Language: English
Learn how to transform text, images, and structured data into high-dimensional vectors and implement efficient search with cosine, Euclidean, and inner product distances. Explore FAISS, Milvus, and Pinecone, and understand the trade-offs between latency, memory, and recall with practical, production-ready Python code.
- Fundamentals of vector embeddings and similarity search
- High-dimensional indexing with FAISS HNSW, IVF, and PQ
- Using managed and self-hosted vector databases
- Building semantic search engines and recommendation systems
- Mathematical insights behind performance optimization
- Semantic search beyond keyword queries
- Personalized recommendations and content retrieval
- Multimodal search with text and images
- RAG pipelines for AI applications
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