Your cart is empty 
Vector databases have become the critical infrastructure layer of modern AI, powering semantic search, recommendation systems, image recognition, and retrieval-augmented generation at scale. Ultimate Milvus Vector Database for AI Apps provides a comprehensive, hands-on guide to building production-grade AI applications using Milvus, the leading open-source vector database, combining mathematical foundations with practical engineering depth. You begin with the core mathematics of AI and deep learning, then progress through the architecture of vector databases, embedding models, and similarity search APIs. The book covers how Milvus manages vector indices, handles large-scale data ingestion, and integrates with modern AI pipelines, including LLMs and generative AI workflows. Every concept is grounded in implementation, from building and training models to deploying production-ready vector search systems. The final sections address distributed index and query management, GPU-accelerated AI, proxy server design, and enterprise network architecture. Thus, by the end of the book, you can design and deploy scalable AI applications using Milvus with confidence, understanding both the theoretical foundations and the engineering decisions that make vector search systems reliable and performant at scale.
Prashanth Raghu works at the intersection of semiconductor architecture, artificial intelligence, and foundational logic systems. As CEO of Sudarshana Semiconductors, his prime focus is on building original compute and reasoning architectures, spanning ASIC design, ML acceleration, and next-generation processing paradigms. His works emphasize first-principles thinking, long-horizon engineering, and technologies that are difficult to replicate without deep technical grounding.
Sneak Preview
