Machine Learning in Finance

  1. Implementation and Production Systems
    1. MLOps for Finance
      1. Model Lifecycle Management
        1. Version Control
          1. Experiment Tracking
            1. Model Registry
            2. Deployment Strategies
              1. Batch Prediction
                1. Real-Time Inference
                  1. A/B Testing
                  2. Infrastructure Requirements
                    1. Computing Resources
                      1. Data Storage
                        1. Network Latency
                        2. Monitoring and Maintenance
                          1. Model Performance Tracking
                            1. Data Drift Detection
                              1. Model Retraining
                            2. Technology Stack
                              1. Programming Languages
                                1. Python Ecosystem
                                  1. R for Statistics
                                    1. C++ for Performance
                                    2. Machine Learning Frameworks
                                      1. Scikit-learn
                                        1. TensorFlow
                                          1. PyTorch
                                            1. XGBoost
                                            2. Data Processing Tools
                                              1. Pandas
                                                1. NumPy
                                                  1. Apache Spark
                                                    1. Dask
                                                    2. Deployment Technologies
                                                      1. Docker Containers
                                                        1. Kubernetes
                                                          1. Cloud Platforms
                                                            1. API Development
                                                          2. Data Management
                                                            1. Data Architecture
                                                              1. Data Lakes
                                                                1. Data Warehouses
                                                                  1. Real-Time Streaming
                                                                  2. Data Quality Management
                                                                    1. Data Validation
                                                                      1. Data Lineage
                                                                        1. Data Governance
                                                                        2. Security and Privacy
                                                                          1. Data Encryption
                                                                            1. Access Controls
                                                                              1. Privacy Preservation

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                                                                          7. Model Development and Validation

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                                                                          9. Regulatory Framework and Ethics