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Vector Databases: The Engine of the AI Revolution
Paperback
Publisher: Independently Published
Published: Sep 10 2025
Pages: 226
Weight: 0.68
Height: 0.48 Width: 6.00 Depth: 9.00
Language: English
3. Software Developers and Architects who need to integrate semantic search or RAG capabilities into their applications.
4. Academics and Researchers seeking a consolidated resource on the principles and practices of vector data management. Key Features of This Book: 1. Beginner to Advanced Progression: The book is structured to guide learners smoothly from foundational concepts to advanced, production-level topics, making it suitable for both novices and experienced practitioners.
2. Practical, Hands-On Approach: Every major theoretical concept is followed by a Hands-On Lab or a practical example, using popular Python libraries and frameworks to solidify understanding.
3. Real-World Case Studies: Chapters are enriched with case studies from leading tech companies, illustrating how vector databases are used to solve real business problems.
4. Simplified Concepts: Complex algorithms and architectures are broken down into simple, easy-to-understand explanations with intuitive analogies and clear diagrams.
5. Complete Capstone Project: The final chapter provides a complete, line-by-line guide to building a fully functional AI-powered Q&A application, integrating all the concepts learned throughout the book.
6. Covers the Latest Technologies: The book covers the most relevant and widely used vector databases (Milvus, Pinecone, Weaviate, Chroma), algorithms (HNSW), and frameworks (LangChain), ensuring the content is up-to-date and industry-relevant. The book takes a first-principles approach, starting with the fundamental concepts of data, meaning, and vector embeddings, and progressively builds up to advanced topics like distributed database architecture and Retrieval-Augmented Generation (RAG). Its pedagogy is rooted in the hands-on, problem-solving ethos, ensuring that students not only understand the theory but can also apply it to build real-world, intelligent systems.
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