Building Intelligent Systems with Knowledge Graphs: Tools, Techniques, and Use Cases

Building Intelligent Systems with Knowledge Graphs: Tools, Techniques, and Use Cases

Overview:
Building Intelligent Systems with Knowledge Graphs is your comprehensive guide to understanding, building, and applying knowledge graphs for modern AI-driven systems. This book demystifies the core concepts behind knowledge graphs, explores the tools and techniques needed for implementation, and provides practical examples for real-world use cases. Whether you're a data scientist, AI engineer, or business professional seeking to leverage connected data for smarter decision-making, this book equips you with the essential skills to design, develop, and deploy intelligent systems powered by knowledge graphs.

By the end of this book, you'll have a deep understanding of how knowledge graphs enhance AI models, support explainable AI (XAI), and enable data-driven insights across industries like healthcare, finance, and smart cities.
This book takes a hands-on approach to teaching knowledge graph concepts, combining theoretical insights with practical tutorials. You'll learn how to build a knowledge graph from scratch, integrate diverse data sources, query data using SPARQL and Cypher, and visualize insights for effective decision-making. Advanced topics like reasoning, entity resolution, and graph-based AI applications are also covered, ensuring you're prepared for both foundational and cutting-edge implementations.

Key Features of This Book:

• Step-by-Step Guidance: Clear, structured tutorials for building and querying knowledge graphs.
• Practical Code Examples: Hands-on coding with SPARQL, Cypher, and graph tools like Neo4j and Amazon Neptune.
• Real-World Use Cases: Explore how knowledge graphs power AI in industries such as healthcare, finance, and smart cities.
• Advanced Topics: Learn about entity resolution, reasoning, and graph-based explainable AI (XAI).
• Scalable Solutions: Understand how to design and deploy large-scale knowledge graphs in distributed environments.

Target Audience:

• AI and Data Professionals: Data scientists, machine learning engineers, and AI researchers seeking to enhance model performance with structured data.
• Business and Domain Experts: Decision-makers and industry professionals aiming to leverage graph technology for smarter insights.
• Software Engineers and Developers: Engineers looking to implement knowledge graphs in modern applications.
• Students and Researchers: Academics exploring the role of graphs in data science and artificial intelligence.

Unlock the power of connected data! Start your journey with Building Intelligent Systems with Knowledge Graphs today and discover how to transform raw information into actionable insights for your AI-driven projects. Whether you're just starting or expanding your expertise, this book is your essential companion for mastering the world of knowledge graphs.