Machine Learning for Developers

  1. Advanced Topics and Specializations
    1. Ensemble Methods
      1. Bagging Techniques
        1. Boosting Techniques
          1. Stacking Methods
            1. Voting Classifiers
            2. Time Series Analysis
              1. Time Series Components
                1. Forecasting Methods
                  1. Seasonal Decomposition
                    1. ARIMA Models
                    2. Recommendation Systems
                      1. Collaborative Filtering
                        1. Content-Based Filtering
                          1. Hybrid Approaches
                            1. Evaluation Metrics
                            2. Anomaly Detection
                              1. Statistical Methods
                                1. Machine Learning Methods
                                  1. Deep Learning Methods
                                    1. Evaluation Challenges
                                    2. Optimization and Hyperparameter Tuning
                                      1. Grid Search
                                        1. Random Search
                                          1. Bayesian Optimization
                                            1. Evolutionary Algorithms
                                            2. Distributed Machine Learning
                                              1. Data Parallelism
                                                1. Model Parallelism
                                                  1. Federated Learning
                                                    1. Edge Computing

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                                                  12. Responsible AI and Ethics

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                                                  1. Introduction to Machine Learning for Developers