Networks in Motion
How Network Science Shapes Better Decisions in AI and Machine Learning
Make smarter decisions by understanding the hidden networks that shape outcomes in AI and machine learning. Network science reveals how connections matter as much as individual data points—and how to leverage that insight for better predictions and decisions. This book teaches you to see systems as networks, apply graph theory to real problems, and build machine learning models that account for relational structure. You'll learn practical frameworks for mapping decision networks, identifying influential nodes, detecting communities, and predicting cascading effects. Whether you're optimizing recommendation systems, improving organizational decisions, or building more robust AI models, network thinking provides the missing perspective that transforms how you approach complex problems. Grounded in both theory and application, this guide makes network science accessible and immediately useful for practitioners working at the intersection of data science, AI, and decision-making.
Est. Length
207 pages (10 chapters)
Language
English
Publication date
Dec 2, 2025
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