Data Mining and Knowledge Discovery

  1. Ethics, Privacy, and Security
    1. Ethical Considerations
      1. Algorithmic Fairness
        1. Fairness Definitions
          1. Bias Sources
            1. Fairness Metrics
              1. Bias Mitigation Techniques
              2. Transparency and Accountability
                1. Social Impact Assessment
                  1. Responsible AI Principles
                  2. Privacy Protection
                    1. Data Anonymization Techniques
                      1. K-Anonymity
                        1. L-Diversity
                          1. T-Closeness
                          2. Differential Privacy
                            1. Privacy Budget
                              1. Noise Addition Mechanisms
                                1. Privacy-Utility Tradeoffs
                                2. Federated Learning
                                  1. Homomorphic Encryption
                                  2. Security Considerations
                                    1. Data Security
                                      1. Encryption at Rest
                                        1. Encryption in Transit
                                          1. Access Control Systems
                                          2. Model Security
                                            1. Adversarial Attacks
                                              1. Model Inversion Attacks
                                                1. Membership Inference Attacks
                                                2. Secure Multi-Party Computation
                                                  1. Audit Trails and Compliance

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                                                11. Deployment and Production Systems

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                                                1. Introduction to Data Mining and Knowledge Discovery