Tutorials
=========

Runnable notebooks that teach the library by example. Each one renders here with
its saved outputs and can be launched interactively on Colab or Binder using the
badges at the top of the notebook. Start with the getting-started pair, then use
the decision guide to choose a method; the remaining sections go deeper on each
method family and on uncertainty quantification.

.. nbgallery::
   :caption: Getting started
   :name: tutorials-getting-started

   AA_datasets_and_dgps
   quickstart

.. nbgallery::
   :caption: Choosing a method
   :name: tutorials-decision-guide

   which_bootstrap_when
   cheat_sheet

.. nbgallery::
   :caption: Core methods
   :name: tutorials-core-methods

   observation_resampling
   residual_and_sieve
   multivariate_var

.. nbgallery::
   :caption: Uncertainty quantification
   :name: tutorials-uq

   enbpi_and_calibrators
   adaptive_drift_aci_nexcp
   forecast_intervals

.. nbgallery::
   :caption: Ecosystem and scaling
   :name: tutorials-integration

   sktime_adapters
   exogenous_regressors
   provenance_and_scaling