9798277976357 - next-gen vector databases: hands-on techniques for high-dimensional search, multimodal retrieval, and ai-powered applications.: 2 di zhou, lian (11 risultati)
Lingua: Inglese
Editore: Independently published, 2025
Serie: Libro 2 di 2 - Vector Database Mastery: From Foundations to Production-Ready AI Search Systems
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Editore: Independently Published, 2025
Serie: Libro 2 di 2 - Vector Database Mastery: From Foundations to Production-Ready AI Search Systems
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Paperback. Condizione: New.
Lingua: Inglese
Editore: Independently published, 2025
Serie: Libro 2 di 2 - Vector Database Mastery: From Foundations to Production-Ready AI Search Systems
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Lingua: Inglese
Editore: Amazon Digital Services LLC - Kdp, 2025
Serie: Libro 2 di 2 - Vector Database Mastery: From Foundations to Production-Ready AI Search Systems
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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Lingua: Inglese
Editore: Amazon Digital Services LLC - Kdp, 2025
Serie: Libro 2 di 2 - Vector Database Mastery: From Foundations to Production-Ready AI Search Systems
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PAP. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
Lingua: Inglese
Editore: Independently published, 2025
Serie: Libro 2 di 2 - Vector Database Mastery: From Foundations to Production-Ready AI Search Systems
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Lingua: Inglese
Editore: Independently published, 2025
Serie: Libro 2 di 2 - Vector Database Mastery: From Foundations to Production-Ready AI Search Systems
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Lingua: Inglese
Editore: Independently Published, 2025
Serie: Libro 2 di 2 - Vector Database Mastery: From Foundations to Production-Ready AI Search Systems
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Paperback. Condizione: new. Paperback. Next-Gen Vector Databases: Hands-On Techniques for High-Dimensional Search, Multimodal Retrieval, and AI-Powered Applications is your definitive guide to building the next generation of intelligent, scalable, and production-ready vector search systems. Designed for engineers, data scientist…s, and AI researchers, this book takes you beyond the fundamentals and dives deep into advanced vector database architectures, cutting-edge retrieval strategies, and real-world AI applications.In this book, you'll explore: High-Dimensional Vector Spaces: Master the mathematical foundations of embeddings, distance metrics, and dimensionality reduction.Adaptive and Distributed Indexing: Implement HNSW, IVF, PQ, and hybrid indices for real-time, large-scale search.Multimodal Retrieval: Integrate text, images, audio, and video into unified vector spaces for AI-powered search.Neural and Retrieval-Augmented Generation (RAG): Combine vector search with LLMs to build next-level chatbots, recommendation engines, and knowledge systems.Edge and Federated Search: Deploy AI search pipelines across distributed environments with privacy-preserving embeddings.Performance, Security, and Optimization: Scale, accelerate, and secure your vector database infrastructure for production workloads.With 40+ hands-on Python examples, this book equips you to implement high-performance pipelines, optimize latency and memory, and handle real-world challenges in multimodal retrieval and RAG workflows. Whether you're building semantic search engines, AI chatbots, recommendation systems, or cutting-edge generative AI applications, this book gives you the tools, techniques, and insights to succeed.Why This Book?Advanced, code-first guidance for modern vector search systemsProduction-ready design patterns with security and compliance best practicesDeep dive into neural retrieval, adaptive indexing, and multimodal pipelinesReal-world use cases across search, recommendation, AI, and generative applicationsWho Should Read This Book: AI and ML engineers building large-scale search and recommendation systemsData scientists integrating vector retrieval into analytics and pipelinesDevOps professionals deploying distributed, high-performance vector databasesResearchers exploring retrieval-augmented generation, multimodal search, and next-gen AI applicationsTake your vector search skills to the next level and master next-generation AI retrieval systems with practical Python examples, mathematical rigor, and production-ready best practices. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Lingua: Inglese
Editore: Independently published, 2025
Serie: Libro 2 di 2 - Vector Database Mastery: From Foundations to Production-Ready AI Search Systems
- Brossura
- Print on Demand
Da: California Books, Miami, FL, U.S.A.California Books
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EUR 18,72
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Condizione: New. Print on Demand.
Altre immaginiLingua: Inglese
Editore: Independently Published, 2025
Serie: Libro 2 di 2 - Vector Database Mastery: From Foundations to Production-Ready AI Search Systems
- Brossura
Da: Rarewaves.com UK, London, Regno UnitoRarewaves.com UK
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 17,03
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Paperback. Condizione: New.
Lingua: Inglese
Editore: Independently Published, 2025
Serie: Libro 2 di 2 - Vector Database Mastery: From Foundations to Production-Ready AI Search Systems
- Brossura
- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
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EUR 21,60
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Paperback. Condizione: new. Paperback. Next-Gen Vector Databases: Hands-On Techniques for High-Dimensional Search, Multimodal Retrieval, and AI-Powered Applications is your definitive guide to building the next generation of intelligent, scalable, and production-ready vector search systems. Designed for engineers, data scientist…s, and AI researchers, this book takes you beyond the fundamentals and dives deep into advanced vector database architectures, cutting-edge retrieval strategies, and real-world AI applications.In this book, you'll explore: High-Dimensional Vector Spaces: Master the mathematical foundations of embeddings, distance metrics, and dimensionality reduction.Adaptive and Distributed Indexing: Implement HNSW, IVF, PQ, and hybrid indices for real-time, large-scale search.Multimodal Retrieval: Integrate text, images, audio, and video into unified vector spaces for AI-powered search.Neural and Retrieval-Augmented Generation (RAG): Combine vector search with LLMs to build next-level chatbots, recommendation engines, and knowledge systems.Edge and Federated Search: Deploy AI search pipelines across distributed environments with privacy-preserving embeddings.Performance, Security, and Optimization: Scale, accelerate, and secure your vector database infrastructure for production workloads.With 40+ hands-on Python examples, this book equips you to implement high-performance pipelines, optimize latency and memory, and handle real-world challenges in multimodal retrieval and RAG workflows. Whether you're building semantic search engines, AI chatbots, recommendation systems, or cutting-edge generative AI applications, this book gives you the tools, techniques, and insights to succeed.Why This Book?Advanced, code-first guidance for modern vector search systemsProduction-ready design patterns with security and compliance best practicesDeep dive into neural retrieval, adaptive indexing, and multimodal pipelinesReal-world use cases across search, recommendation, AI, and generative applicationsWho Should Read This Book: AI and ML engineers building large-scale search and recommendation systemsData scientists integrating vector retrieval into analytics and pipelinesDevOps professionals deploying distributed, high-performance vector databasesResearchers exploring retrieval-augmented generation, multimodal search, and next-gen AI applicationsTake your vector search skills to the next level and master next-generation AI retrieval systems with practical Python examples, mathematical rigor, and production-ready best practices. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
