Preface
1. Why Learn the Mathematics of AI
2. Data, Data, Data
3. Fitting Functions to Data
4. Optimization for Neural Networks
5. Convolutional Neural Networks and Computer Vision
6. Singular Value Decomposition: Image Processing, Natural Language Processing and Social Media
7. Natural Language and Finance AI: Vectorization and Time Series
8. Probabilistic Generative Models
9. Graph Models
10. Operations Research
11. Probability
12. Mathematical Logic
13. Artificial Intelligence and Partial Differential Equations
14. Artificial Intelligence, Ethics, Mathematics, Law, and Policy
