GluonTS: Probabilistic Time Series Models in Python

TL;DR

GluonTS is a Python library that streamlines the development, experimentation, and evaluation of deep learning models for time series forecasting and anomaly detection.

Contribution

It provides comprehensive tools and components that facilitate rapid model development and analysis in time series tasks.

Findings

Enables quick development of new models

Supports efficient experimentation and evaluation

Simplifies time series analysis workflows

Abstract

We introduce Gluon Time Series (GluonTS, available at https://gluon-ts.mxnet.io), a library for deep-learning-based time series modeling. GluonTS simplifies the development of and experimentation with time series models for common tasks such as forecasting or anomaly detection. It provides all necessary components and tools that scientists need for quickly building new models, for efficiently running and analyzing experiments and for evaluating model accuracy.