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{ "item_title" : "Ultimate Milvus Vector Database for AI Apps", "item_author" : [" Prashanth Raghu "], "item_description" : "Build Production AI Systems Using the World's Leading Vector DatabaseBook DescriptionVector 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.What you will learn● Understand the mathematical foundations of vectors and AI that underpin modern intelligent applications.● Design and build vector indices using Milvus to power accurate similarity search at production scale.● Implement binary, sparse, and GPU-accelerated index types to optimise Milvus for diverse AI workloads.Who is This Book For?This book is for all AI engineers, ML practitioners, and software architects who want to build scalable AI applications using vector databases. A working knowledge of engineering mathematics, probability theory, Python, and basic database design is expected; no prior Milvus experience is required.Table of Contents1. Introduction to Vector Databases2. Fundamentals of Vectors and AI3. Components of Milvus4. Data, Storage, and Cluster Management5. Indexing Schemes6. Indexing Schemes Binary, Sparse, and GPU7. Distributed Data Management8. Distributed Index and Query Management9. Design of the Proxy Server10. GPU-Based Indexes and Optimizations11. Auxiliary Components12. Network Management Index", "item_img_path" : "https://covers4.booksamillion.com/covers/bam/9/34/988/718/9349887185_b.jpg", "price_data" : { "retail_price" : "44.95", "online_price" : "44.95", "our_price" : "44.95", "club_price" : "44.95", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Ultimate Milvus Vector Database for AI Apps|Prashanth Raghu

Ultimate Milvus Vector Database for AI Apps

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Overview

Build Production AI Systems Using the World's Leading Vector Database

Book Description

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.

What you will learn

● Understand the mathematical foundations of vectors and AI that underpin modern intelligent applications.

● Design and build vector indices using Milvus to power accurate similarity search at production scale.

● Implement binary, sparse, and GPU-accelerated index types to optimise Milvus for diverse AI workloads.

Who is This Book For?

This book is for all AI engineers, ML practitioners, and software architects who want to build scalable AI applications using vector databases. A working knowledge of engineering mathematics, probability theory, Python, and basic database design is expected; no prior Milvus experience is required.

Table of Contents

1. Introduction to Vector Databases

2. Fundamentals of Vectors and AI

3. Components of Milvus

4. Data, Storage, and Cluster Management

5. Indexing Schemes

6. Indexing Schemes Binary, Sparse, and GPU

7. Distributed Data Management

8. Distributed Index and Query Management

9. Design of the Proxy Server

10. GPU-Based Indexes and Optimizations

11. Auxiliary Components

12. Network Management

Index

This item is Non-Returnable

Details

  • ISBN-13: 9789349887183
  • ISBN-10: 9349887185
  • Publisher: Orange Education Pvt Ltd
  • Publish Date: April 2026
  • Dimensions: 9.25 x 7.5 x 0.55 inches
  • Shipping Weight: 1 pounds
  • Page Count: 260

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