# Examples¶

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.

## 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¶

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:

## 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: