Machine Learning for Developers

  1. Machine Learning Project Lifecycle
    1. Problem Definition and Scoping
      1. Business Objective Identification
        1. Stakeholder Requirements Analysis
          1. Success Criteria Definition
            1. Feasibility Assessment
              1. Resource Planning
              2. Problem Formulation
                1. Business to Technical Translation
                  1. ML Problem Type Selection
                    1. Target Variable Definition
                      1. Constraint Identification
                        1. Baseline Establishment
                        2. Data Strategy and Acquisition
                          1. Data Requirements Analysis
                            1. Internal Data Sources
                              1. External Data Sources
                                1. Data Collection Planning
                                  1. Data Quality Assessment
                                  2. Data Preparation and Engineering
                                    1. Data Exploration and Profiling
                                      1. Data Cleaning and Validation
                                        1. Feature Engineering
                                          1. Data Transformation
                                            1. Data Splitting Strategies
                                            2. Model Development Process
                                              1. Algorithm Selection
                                                1. Model Architecture Design
                                                  1. Training Strategy
                                                    1. Hyperparameter Optimization
                                                      1. Model Validation
                                                      2. Evaluation and Testing
                                                        1. Performance Metrics Selection
                                                          1. Cross-Validation Strategies
                                                            1. Statistical Significance Testing
                                                              1. Business Impact Assessment
                                                                1. Error Analysis
                                                                2. Deployment Planning
                                                                  1. Infrastructure Requirements
                                                                    1. Serving Architecture Design
                                                                      1. Performance Requirements
                                                                        1. Scalability Considerations
                                                                          1. Monitoring Strategy

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                                                                        1. Introduction to Machine Learning for Developers

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                                                                        3. Supervised Learning Fundamentals