GluonTS - Probabilistic Time Series Modeling

Gluon Time Series (GluonTS) is the Gluon toolkit for probabilistic time series modeling, focusing on deep learning-based models.

GluonTS provides utilities for loading and iterating over time series datasets, state of the art models ready to be trained, and building blocks to define your own models and quickly experiment with different solutions. With GluonTS you can:

  • Train and evaluate any of the built-in models on your own data, and quickly come up with a solution for your time series tasks.

  • Use the provided abstractions and building blocks to create custom time series models, and rapidly benchmark them against baseline algorithms.

Get Started: A Quick Example

Here is a simple time series example with GluonTS for predicting Twitter volume with DeepAR.

(You can click the play button below to run this example.)


You can install GluonTS using pip simply by running

pip install gluonts


For more detailed guide on installing GluonTS, click the install link in the top navigation bar.


The best way to get started with GluonTS is by diving in using our tutorials, which you can download as Jupyter notebooks.