Chapter 1. Introduction. Chapter 2. Manufacturing. Chapter 3. Telecommunications. Chapter 4. Health care. Chapter 5. Insurance. Chapter 6.Financial services. Chapter 7. Professional services. Chapter 8. Travel. Chapter 9. E-commerce models. Chapter 10. Using the industry medels in the real world.
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The data model resource book : vol 3 : universal patterns for data modeling
Chapter 1: Introduction. Chapter 2. Setting up roles: What parties do. Chapter 3. Using roles: How parties are involved. Hierarchies, aggregations, and peer-to-peer relationship: The organization of similar data. Chapter 5. Types and catergories: The classification of data. Chapter 6. Status: The ...
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The elements of statistical learning : data mining, inference, and prediction : 2nd ed.
Contents: 1. Introduction; 2. Overview of supervised learning; 3. Linear methods for regression; 4. Linear methods for classification; 5. Basis expansions and regularization; 6. Kernel smoothing methods; 7. Model assessment and selection; 8. Model inference and averaging; 9. Additive models, trees, ...
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Introduction to probability : 2nd ed.
Contents: 1. Sample space and probability; 2. Discrete random variables; 3. General random variables; 4. Further topics on random variables; 5. The Bernoulli and Poisson processes; 6. Markov chains; 7. Limit theorems.
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Applied linear regression models : 4th ed.
Part I. Simple linear regression; Part II. Multiple linear regression; Part III. Nonlinear regression.
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