Khoa Công Nghệ Thông Tin
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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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Software quality assurance : from theory to implementation
Part 1: Introduction. Part 2: Pre-project software quality components. Part 3: SQA components in the project life cycle. Part 4: Software quality infrastructure components. Part 5: Management components of software quality. Part 5: Standards, certification and assessment. Part 6: Organization for ...
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Metrics and models in software quality engineering : 2nd ed.
What is software quality. Software development process models. Fundamentals of measurement theory. Software quality metrics overview. Applying the seven basic quality tool in software development. Defect removal efectiveness. The rayleigh model. Exponential distribution and reliability growth ...
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