AI for Business

  1. The AI Implementation Lifecycle
    1. Business and Data Understanding
      1. Business Problem Definition
        1. Stakeholder Analysis and Engagement
          1. Data Exploration and Profiling
            1. Success Criteria Definition
            2. Model Development and Experimentation
              1. Algorithm Selection
                1. Selection Criteria
                  1. Algorithm Benchmarking
                    1. Performance Trade-offs
                    2. Model Training and Optimization
                      1. Hyperparameter Tuning
                        1. Cross-Validation Strategies
                          1. Overfitting Prevention
                            1. Model Ensemble Techniques
                          2. Model Evaluation and Validation
                            1. Technical Performance Metrics
                              1. Classification Metrics
                                1. Accuracy
                                  1. Precision
                                    1. Recall
                                      1. F1 Score
                                      2. Regression Metrics
                                        1. Mean Squared Error
                                          1. Mean Absolute Error
                                            1. R-squared
                                            2. Advanced Metrics
                                              1. Area Under Curve
                                                1. Confusion Matrix Analysis
                                              2. Business Impact Assessment
                                                1. Business Objective Alignment
                                                  1. Cost-Benefit Analysis
                                                    1. Stakeholder Validation
                                                  2. Model Deployment and MLOps
                                                    1. Production Integration
                                                      1. Software System Integration
                                                        1. Workflow Automation
                                                          1. API Development
                                                          2. Deployment Patterns
                                                            1. Batch Processing
                                                              1. Real-Time Inference
                                                                1. Edge Deployment
                                                                2. Infrastructure Considerations
                                                                  1. Cloud vs. On-Premise
                                                                    1. Scalability Requirements
                                                                      1. Performance Optimization
                                                                    2. Monitoring and Maintenance
                                                                      1. Performance Monitoring
                                                                        1. Real-Time Dashboards
                                                                          1. Automated Alerting
                                                                            1. Performance Degradation Detection
                                                                            2. Model Drift Management
                                                                              1. Data Drift Detection
                                                                                1. Concept Drift Monitoring
                                                                                  1. Statistical Testing Methods
                                                                                  2. Model Lifecycle Management
                                                                                    1. Retraining Strategies
                                                                                      1. Model Versioning
                                                                                        1. A/B Testing Frameworks

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                                                                                    4. Data: The Foundation of Business AI

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                                                                                    6. Functional Applications of AI Across the Enterprise