Time Series Analysis

  1. Machine Learning for Time Series
    1. Feature Engineering
      1. Lag Features
        1. Rolling Window Features
          1. Date and Time Features
            1. Fourier Features
              1. Wavelet Features
              2. Regression Approaches
                1. Linear Regression
                  1. Regularized Regression
                    1. Polynomial Regression
                      1. Spline Regression
                      2. Tree-Based Methods
                        1. Decision Trees
                          1. Random Forest
                            1. Gradient Boosting
                              1. XGBoost
                                1. LightGBM
                                2. Support Vector Machines
                                  1. SVM for Regression
                                    1. Kernel Methods
                                      1. Parameter Tuning
                                      2. Neural Networks
                                        1. Feedforward Networks
                                          1. Recurrent Neural Networks
                                            1. LSTM Networks
                                              1. GRU Networks
                                                1. Convolutional Neural Networks
                                                2. Deep Learning Architectures
                                                  1. Encoder-Decoder Models
                                                    1. Attention Mechanisms
                                                      1. Transformer Models
                                                        1. Temporal Convolutional Networks
                                                        2. Ensemble Methods
                                                          1. Model Averaging
                                                            1. Stacking
                                                              1. Boosting for Time Series

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                                                            12. State Space Models and Kalman Filtering

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                                                            14. Forecasting Evaluation and Model Selection