{"product_id":"vector-database-deep-dive-cameron-mclucas-9798296370396","title":"Vector Database Deep Dive: Optimize AI Workflows for Speed, Accuracy, and Enterprise Scale","description":"\u003cp\u003e\u003cb\u003eVector Database Deep Dive: Optimize AI Workflows for Speed, Accuracy, and Enterprise Scale\u003c\/b\u003e\u003c\/p\u003e\u003cp\u003eWhy do some AI systems scale effortlessly while others collapse under pressure? Why do high-performing models still return irrelevant results? The answer often lies not in the models-but in the databases powering them.\u003c\/p\u003e\u003cp\u003e\u003ci\u003eVector Database Deep Dive\u003c\/i\u003e confronts one of the most pressing challenges in AI engineering today: how to manage high-dimensional data at speed and scale without compromising precision. 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.\u003c\/p\u003e\u003cp\u003eBuilt on real-world use cases and production-ready practices, this book equips you with a modern, system-level understanding of how vector databases drive AI performance. Whether you're building intelligent chat systems, scaling recommendation engines, or supporting multimodal embeddings, you'll learn how to architect, optimize, and integrate vector stores for maximum impact.\u003c\/p\u003e\u003cp\u003e\u003cb\u003eInside, you'll master: \u003c\/b\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003e\u003cp\u003eStructuring high-dimensional data for fast approximate nearest neighbor (ANN) search\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eIndexing and filtering strategies for hybrid retrieval at scale\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eReal-time ingestion, chunking, and embedding workflows with tools like FAISS, Qdrant, Milvus, Weaviate, and Elasticsearch\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eVector store evaluation frameworks for latency, recall, and throughput\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eMemory-augmented applications and context window optimization using vector-backed architectures\u003c\/p\u003e\u003c\/li\u003e\n\u003cli\u003e\u003cp\u003eScaling strategies for production deployments, from fine-tuning ingestion pipelines to sharding and horizontal scaling\u003c\/p\u003e\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003eYou won't just gain theory-you'll build, deploy, and optimize live vector-based systems from the ground up, with clear code examples and deployment scenarios.\u003c\/p\u003e\u003cp\u003eIf you're an AI engineer, data architect, or software developer responsible for production ML systems, this book delivers the hands-on frameworks, mental models, and best practices you need to lead in the AI era.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Cameron McLucas\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9798296370396\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Independently Published\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 08\/03\/2025\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 182\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 0.72lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 10.00h x 7.00w x 0.39d","brand":"Cameron McLucas","offers":[{"title":"Paperback","offer_id":47520815775999,"sku":"9798296370396","price":20.0,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0662\/2982\/9887\/files\/img_cf3275ca-8286-406f-a1c0-be6b2089886f.jpg?v=1762887212","url":"https:\/\/www.whiterainbookhouse.com\/products\/vector-database-deep-dive-cameron-mclucas-9798296370396","provider":"WR Book House","version":"1.0","type":"link"}