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NeuralProphet 1.0.0rc8 documentation
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  • Quick Start Guide

Tutorials

  • Tutorials
    • 01: The Basics
    • 02: Trends
    • 03: Seasonality
    • 04: Auto Regression
    • 05: Lagged Regressors
    • 06: Future Regressors
    • 07: Events and Holidays
    • 08: Uncertainty
    • 09: Global Model
    • 10: Validation and Reproducibility
    • 11: Next Steps

How To Guides

  • Feature guides
    • Collect Predictions
    • Testing and Cross Validation
    • Plotting
    • Global Local Modelling
    • Uncertainty Quantification
    • Conditional Seasonality
    • Multiplicative Seasonality
    • Sparse Autoregression
    • Subdaily data
    • Hyperparameter Selection
    • MLflow Integration
    • Live Plotting during Training
    • Network Architecture Visualization
  • Application examples
    • Power Demand: Forecasting Load for a Hospital in SF
    • Renewable Energy: Forecasting Solar
    • Forecasting energy load with visualization
  • Migrate From Prophet
    • Migration from Prophet
    • Prophet to TorchProphet

Code Documentation

  • NeuralProphet
    • forecaster.py (NeuralProphet)
    • configure.py
    • time_dataset.py
    • time_net.py
    • torch_prophet.py
    • uncertainty.py
    • data/process.py
    • data/split.py
    • data/transform.py
    • components/router.py
    • components/base.py
    • components/future_regressors
    • components/seasonality
    • components/trend
    • plot_forecast_plotly.py
    • plot_forecast_matplotlib.py
    • plot_model_parameters_plotly.py
    • plot_model_parameters_matplotlib.py
    • utils.py
    • df_utils.py
    • hdays_utils.py
    • plot_utils.py
    • utils_metrics.py
    • utils_torch.py
    • custom_loss_metrics.py
    • logger.py
    • np_types.py

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