Here you will find some example notebooks to get more familiar with the Darts’ API. All the notebooks are also available in ipynb format directly on github.

Multiple Time Series, Pre-trained Models and Covariates

Example notebook on training with multiple time series, pre-trained models and using covariates:

Data (pre) Processing

Data processing example notebook:

Static Covariates

Static covariates example notebook:

Transfer Learning Tutorial

A self-contained notebook showcasing examples of training some bigger models on large datasets of time series, and using such models to forecast new time series that have not been seen during training:

Hierarchical Reconciliation

A self-contained notebook showcasing how to reconcile forecasts for hierarchical time series, using the Australian domestic tourism dataset.

Hyperparameter Optimization

An example showcasing how to find good forecasting models with Darts using the Optuna library for hyperparameter optimization.

Regression Models

Regression models example notebook:

Fast Fourier Transform

FFT model example notebook:

Recurrent Neural Networks

RNN model example notebook:

Temporal Convolutional Networks

TCN model example notebook:

Transformer Model

Transformer model example notebook:


N-BEATS model example notebook:

DeepAR Model

DeepAR model example notebook:

DeepTCN Model

DeepTCN model example notebook:

Temporal Fusion Transformer (TFT) Model

TFT model example notebook:

TimeSeries Dense Encoder (TiDE) Model

TiDE model example notebook:

TimeSeries Mixer (TSMixer) Model

TSMixer model example notebook:

Ensemble Models

Ensemble models example notebook:

Kalman Filter Model

Kalman filter model example notebook:

Gaussian Process Filter Model

Gaussian process filter model example notebook:

Dynamic Time Warping (DTW)

Dynamic time warping example notebook: