
Category Theory for AI: A Gentle, Concrete Introduction to Compositional Thinking for Machine Learning and Intelligent Systems
Lukas Moretti
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Opening Credits
1/11/2026
Chapter 1: Why AI Needs Better Abstractions
1/11/2026
Chapter 2: From Functions to Arrows Seeing Structure in Simple Maps
1/11/2026
Chapter 3: What Is a Category Worlds of Things and Processes
1/11/2026
Chapter 4: Drawing Categories Diagrams as Maps of AI Workflows
1/11/2026
Chapter 5: Combining Information Products, Coproducts, and Simple Merges
1/11/2026
Chapter 6: Functors Mapping Structures Between Worlds
1/11/2026
Chapter 7: Natural Transformations Comparing Different Ways of Doing the Same Thing
1/11/2026
Chapter 8: Monoidal Categories and String Diagrams A Visual Language for Architectures
1/11/2026
Chapter 9: Functorial Semantics Linking Data, Models, and Meaning
1/11/2026
Chapter 10: Compositional Case Studies and a Roadmap for Practice
1/11/2026
Closing Credits
1/11/2026