Machine Learning Fundamentals

  1. Practical Considerations
    1. Ethical Implications in Machine Learning
      1. Bias and Fairness
        1. Sources of Bias
          1. Historical Bias
            1. Representation Bias
              1. Measurement Bias
                1. Evaluation Bias
                2. Mitigation Strategies
                  1. Diverse Data Collection
                    1. Algorithmic Fairness
                      1. Bias Testing
                        1. Inclusive Design
                        2. Fairness Metrics
                          1. Demographic Parity
                            1. Equalized Odds
                              1. Individual Fairness
                            2. Privacy
                              1. Data Anonymization
                                1. De-identification Techniques
                                  1. K-Anonymity
                                    1. Differential Privacy
                                    2. Data Security
                                      1. Encryption Methods
                                        1. Access Controls
                                          1. Secure Computation
                                        2. Accountability
                                          1. Explainability
                                            1. Model Interpretability
                                              1. Feature Importance
                                                1. Decision Explanations
                                                2. Transparency
                                                  1. Algorithm Documentation
                                                    1. Performance Reporting
                                                      1. Audit Trails
                                                      2. Responsibility
                                                        1. Human Oversight
                                                          1. Error Handling
                                                            1. Impact Assessment
                                                        2. Common Tools and Frameworks
                                                          1. Python Libraries
                                                            1. Scikit-learn
                                                              1. Core Features
                                                                1. Unified API
                                                                  1. Algorithm Implementation
                                                                    1. Preprocessing Tools
                                                                      1. Model Evaluation
                                                                      2. Strengths and Limitations
                                                                      3. Pandas
                                                                        1. Data Manipulation
                                                                          1. DataFrame Operations
                                                                            1. Data Cleaning
                                                                              1. Data Transformation
                                                                              2. File I/O Operations
                                                                              3. NumPy
                                                                                1. Numerical Computation
                                                                                  1. Array Operations
                                                                                    1. Mathematical Functions
                                                                                      1. Linear Algebra
                                                                                      2. Performance Optimization
                                                                                      3. Matplotlib / Seaborn
                                                                                        1. Data Visualization
                                                                                          1. Statistical Plots
                                                                                            1. Customization Options
                                                                                              1. Publication Quality
                                                                                              2. Exploratory Data Analysis
                                                                                            2. R Programming
                                                                                              1. Statistical Computing
                                                                                                1. Specialized Packages
                                                                                                  1. Academic Research Focus
                                                                                                  2. Cloud Platforms
                                                                                                    1. Overview of Major Providers
                                                                                                      1. Amazon Web Services
                                                                                                        1. Google Cloud Platform
                                                                                                          1. Microsoft Azure
                                                                                                          2. Managed ML Services
                                                                                                            1. AutoML Platforms
                                                                                                              1. Model Deployment
                                                                                                                1. Scalable Computing
                                                                                                                2. Cost Considerations
                                                                                                                  1. Pricing Models
                                                                                                                    1. Resource Optimization
                                                                                                                      1. Budget Management
                                                                                                                    2. Development Environments
                                                                                                                      1. Jupyter Notebooks
                                                                                                                        1. Integrated Development Environments
                                                                                                                          1. Version Control Systems
                                                                                                                        2. Pathways for Further Learning
                                                                                                                          1. Community and Online Resources
                                                                                                                            1. Academic Courses
                                                                                                                              1. Online Platforms
                                                                                                                                1. Professional Communities
                                                                                                                                  1. Conferences and Workshops
                                                                                                                                  2. Building a Portfolio
                                                                                                                                    1. Project Selection
                                                                                                                                      1. Documentation Practices
                                                                                                                                        1. Code Quality
                                                                                                                                          1. Presentation Skills
                                                                                                                                            1. GitHub Best Practices

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                                                                                                                                        9. Introduction to Advanced Concepts

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                                                                                                                                        1. Introduction to Machine Learning