Log in to access more pages.
Create an account or log in to continue reading more pages.
Log in
Table of contents
Artificial Intelligence from First Principles
A rigorous, practical path from core ideas to building and evaluating modern AI systems
Read each section in order. Every title can be opened as a TheoryTrace document.
- Cover1
- Copyright2
- How to read this book3
- Introduction4
- Chapter 1: What Artificial Intelligence Is5
- Chapter 2: The Computational View of Intelligence6
- Chapter 3: Essential Mathematics for AI7
- Chapter 4: Data, Features, and Measurement8
- Chapter 5: Learning as Generalization9
- Chapter 6: Supervised Learning10
- Chapter 7: Evaluating AI Models11
- Chapter 8: Unsupervised Learning and Representation12
- Chapter 9: Optimization and Training13
- Chapter 10: Neural Networks14
- Chapter 11: Deep Learning for Vision, Language, and Signals15
- Chapter 12: Natural Language Processing16
- Chapter 13: Large Language Models17
- Chapter 14: Generative AI18
- Chapter 15: Retrieval, Tools, and AI Applications19
- Chapter 16: Reasoning, Planning, and Agents20
- Chapter 17: Reinforcement Learning21
- Chapter 18: Building an AI System End to End22
- Chapter 19: AI Engineering and MLOps23
- Chapter 20: Safety, Security, and Robustness24
- Chapter 21: Ethics, Law, and Social Impact25
- Chapter 22: The Frontier and Your Learning Roadmap26
- Conclusion27