Machine Learning with Scikit-Learn

  1. Advanced Topics
    1. Ensemble Methods
      1. Bagging
        1. Bootstrap Aggregating
          1. Variance Reduction
          2. Boosting
            1. Sequential Learning
              1. Bias Reduction
              2. Stacking
                1. Meta-learning
                  1. Blending
                  2. Voting Classifiers and Regressors
                    1. Hard Voting
                      1. Soft Voting
                    2. Multi-output Learning
                      1. Multi-output Regression
                        1. Multi-output Classification
                          1. Multi-label Classification
                            1. Classifier Chains
                            2. Semi-supervised Learning
                              1. Label Propagation
                                1. Label Spreading
                                  1. Self-training
                                  2. Online Learning
                                    1. Incremental Learning
                                      1. Partial Fit Methods
                                        1. Stream Processing
                                        2. Calibration
                                          1. Probability Calibration
                                            1. Platt Scaling
                                              1. Isotonic Regression
                                              2. Feature Engineering Automation
                                                1. Automated Feature Selection
                                                  1. Feature Construction
                                                  2. Model Interpretation
                                                    1. Feature Importance
                                                      1. Permutation Importance
                                                        1. Partial Dependence Plots
                                                          1. SHAP Values Integration

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                                                        11. Working with Text Data

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                                                        13. Model Persistence and Deployment