models¶

Models for timeseries forecasting.

Modules

`pytorch_forecasting.models.base_model`	Timeseries models share a number of common characteristics.
`pytorch_forecasting.models.baseline`	Baseline model.
`pytorch_forecasting.models.deepar`	DeepAR: Probabilistic forecasting with autoregressive recurrent networks <https://www.sciencedirect.com/science/article/pii/S0169207019301888>`_ which is the one of the most popular forecasting algorithms and is often used as a baseline
`pytorch_forecasting.models.nbeats`	N-Beats model for timeseries forecasting without covariates.
`pytorch_forecasting.models.nn`
`pytorch_forecasting.models.temporal_fusion_transformer`	The temporal fusion transformer is a powerful predictive model for forecasting timeseries

Models base_model