Vector Database Engineering: Building Scalable AI Search & Retrieval Systems with FAISS, Milvus, Pinecone, Weaviate, RAG Pipelines, Embeddings, High Dimension Indexing (with Mathematical Equations)
Vector Database Engineering: Building Scalable AI Search & Retrieval Systems with FAISS, Milvus, Pinecone, Weaviate, RAG Pipelines, Embeddings, High Dimension Indexing (with Mathematical Equations)
Vector Database Engineering is the ultimate guide to designing, building, and deploying scalable vector search systems using tools like FAISS, Milvus, Pinecone, Weaviate, and Qdrant. Whether you're building a semantic search engine, a personalized recommendation system, or an AI-powered chatbot, this book gives you the theoretical foundations, mathematical insights, and production-ready Python code you need to succeed. What You'll Learn Vector Embeddings & Similarity Search: Represent text, images, and data as vectors ...
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Vector Database Engineering is the ultimate guide to designing, building, and deploying scalable vector search systems using tools like FAISS, Milvus, Pinecone, Weaviate, and Qdrant. Whether you're building a semantic search engine, a personalized recommendation system, or an AI-powered chatbot, this book gives you the theoretical foundations, mathematical insights, and production-ready Python code you need to succeed. What You'll Learn Vector Embeddings & Similarity Search: Represent text, images, and data as vectors and retrieve results using cosine, Euclidean, and inner product distances. Vector Indexing at Scale: Implement FAISS HNSW, IVF, and PQ structures. Learn trade-offs between recall and latency. Managed & Distributed Databases: Use managed services like Pinecone and self-hosted options like Milvus, Weaviate, and Qdrant. Real-World Applications: Build semantic search engines, RAG pipelines, multimodal retrieval, recommendation systems, and edge deployments. Security & Compliance: Add RBAC, TLS encryption, audit logging, and GDPR-compliant deletion. Advanced Topics: Explore neural search, adaptive indexing, multimodal embeddings (e.g., CLIP), and federated search. Key Use Cases Semantic Search: Go beyond keywords using AI vector queries. Recommendations: Suggest content and products based on behavior. Multimedia Retrieval: Search images, audio, and video using embeddings. RAG: Feed live vector data into LLMs for better answers. Fraud & Anomaly Detection: Identify outliers with proximity-based search. NLP & Generative AI: Embed, retrieve, and generate content with LLMs. Why This Book? Hands-On Python: 40+ real-world examples with FAISS, Qdrant, Pinecone, Milvus, and Weaviate. Math-Based Optimization: Understand latency, memory, and performance trade-offs. Production Ready: Secure, scalable design patterns with best practices. Future Trends: Includes neural retrievers, adaptive indexing, and multimodal workflows. Who It's For Engineers building real-time search and recommendation engines ML and Data Scientists integrating vector search in pipelines DevOps deploying scalable and secure AI infrastructure AI researchers exploring retrieval-augmented generation Students and builders learning practical vector search This is your in-depth, code-first guide to building intelligent, scalable vector database systems. Start using vector search to power the next generation of AI. Get your copy now.
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Add this copy of Vector Database Engineering: Building Scalable AI to cart. $17.71, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2025 by Independently Published.
Add this copy of Vector Database Engineering: Building Scalable AI to cart. $24.88, like new condition, Sold by GreatBookPrices rated 4.0 out of 5 stars, ships from Columbia, MD, UNITED STATES, published 2025 by Independently Published.
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Fine. Trade paperback (US). Glued binding. 168 p. AI Engineering for Practitioners, 1. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
Add this copy of Vector Database Engineering: Building Scalable AI to cart. $25.13, new condition, Sold by GreatBookPrices rated 4.0 out of 5 stars, ships from Columbia, MD, UNITED STATES, published 2025 by Independently Published.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
New. Trade paperback (US). Glued binding. 168 p. AI Engineering for Practitioners, 1. In Stock. 100% Money Back Guarantee. Brand New, Perfect Condition, allow 4-14 business days for standard shipping. To Alaska, Hawaii, U.S. protectorate, P.O. box, and APO/FPO addresses allow 4-28 business days for Standard shipping. No expedited shipping. All orders placed with expedited shipping will be cancelled. Over 3, 000, 000 happy customers.
