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Probability Theory with a View Toward Machine Learning
1. Probability spaces
2. Rules of probability
3. Random variables
4. Examples of random variables
5. Connecting theory to practice: a first look at model building
6. Random vectors
7. More probability theory
8. The halfway point: pivoting toward models and data analysis
9. Information theory
10. Optimization
11. Probabilistic graphical models
12. Learning
13. Bibliography
Index
