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Examples

We have prepared a set of tutorials for an easy introduction:

01. Get started

  • Creating TSDataset and time series plotting
  • Forecast single time series - Simple forecast, Prophet, Catboost
  • Forecast multiple time series
  • Pipeline

02. Backtest

  • What is backtest and how it works
  • How to run a validation
  • Validation visualisation

03. EDA

  • Visualization
    • Plot
    • Partial autocorrelation
    • Cross-correlation
    • Correlation heatmap
    • Distribution
  • Outliers
    • Median method
    • Density method
  • Change Points
    • Change points plot
    • Interactive change points plot

04. Regressors and exogenous data

  • What is regressor?
    • What is exogenous data?
  • Dataset
    • Loading Dataset
    • EDA
  • Forecast with regressors

05. Custom model and transform

  • What is Transform and how it works
  • Custom Transform
    • Per-segment Custom Transform
    • Multi-segment Custom Transform
  • Custom Model

06. Deep learning models

  • Creating TSDataset
  • Architecture
  • Testing models
    • DeepAR
    • TFT
    • Simple Model

07. Ensembles

  • VotingEnsemble
  • StackingEnsemble

08. Outliers

  • Point outliers
    • Median method
    • Density method
    • Prediction interval method
    • Histogram method
  • Sequence outliers
  • Interactive visualization
  • Outliers imputation

09. Forecasting strategies

  • Imports and constants
  • Load dataset
  • Recursive strategy
    • AutoRegressivePipeline
  • Direct strategy
    • Pipeline
    • DirectEnsemble
    • assemble_pipelines + DirectEnsemble
  • Summary

10. Forecast interpretation

  • Forecast decomposition
    • CatBoost
    • SARIMAX
    • BATS
    • In-sample and out-of-sample decomposition
  • Accessing target components
  • Regressors relevance
    • Feature relevance
    • Components relevance

11. Clustering

  • Clustering pipeline
  • Custom Distance
  • Visualisation

12. AutoML script

  • Auto pipeline search

13. AutoML notebook

  • Hyperparameters tuning
    • How Tune works
    • Example
  • General AutoML
    • How Auto works
    • Example

14. Hyperparameter search

15. Inference: using saved pipeline on a new data

  • Fitting and saving pipeline
  • Using saved pipeline on a new data

16. Hierarchical time series

  • Hierarchical time series
  • Hierarchical structure
  • Reconciliation methods
  • Exogenous variables for hierarchical forecasts

17. Classification

  • Classification
    • Load Dataset
    • Feature extraction
    • Cross validation
  • Predictability analysis
    • Load Dataset
    • Load pretrained analyzer
    • Analyze segments predictability

18. Feature selection

  • Loading Dataset
  • Feature selection methods
    • Intro to feature selection
    • TreeFeatureSelectionTransform
    • GaleShapleyFeatureSelectionTransform
    • MRMRFeatureSelectionTransform