index.rst

Feature guides

Note

The feature guides show how to use specific features of NeuralProphet in detail. For more basic examples, see the tutorial section.

.. toctree::
    :maxdepth: 1

    Collect Predictions<feature-guides/collect_predictions>
    Testing and Cross Validation<feature-guides/test_and_crossvalidate>
    Plotting<feature-guides/plotly>
    Global Local Modelling<feature-guides/global_local_modeling>
    Uncertainty Quantification<feature-guides/uncertainty_quantification>
    Conditional Seasonality<feature-guides/conditional_seasonality_peyton>
    Multiplicative Seasonality<feature-guides/season_multiplicative_air_travel>
    Sparse Autoregression<feature-guides/sparse_autoregression_yosemite_temps>
    Subdaily data<feature-guides/sub_daily_data_yosemite_temps>
    Hyperparameter Selection<feature-guides/hyperparameter-selection>
    MLflow Integration<feature-guides/mlflow>
    Live Plotting during Training<feature-guides/Live_plot_during_training>
    Network Architecture Visualization<feature-guides/network_architecture_visualization>

Application examples

Note

Here you can find examples of how to use NeuralProphet on different datasets.

.. toctree::
    :maxdepth: 1

    Power Demand: Forecasting Load for a Hospital in SF<application-examples/energy_hospital_load>
    Renewable Energy: Forecasting Solar<application-examples/energy_solar_pv>
    Forecasting energy load with visualization<application-examples/energy_tool>

Migrate From Prophet

.. toctree::
   :maxdepth: 1

   Migration from Prophet<feature-guides/Migration_from_Prophet>
   Prophet to TorchProphet<feature-guides/prophet_to_torch_prophet>