GluonTS is a Python package for probabilistic time series modeling, focusing on deep learning based models, based on PyTorch and MXNet.

a “distribution forecast” or “full probabilistic forecast” is a prediction/estimate of the distribution of y ′ | y , e.g., “it's a normal distribution with mean ...

Dec 1, 2022 · Typically, classical methods are fitted on each time series in a dataset individually. These are often referred to as "single" or "local" ...

Nov 26, 2020 · Perform probabilistic time series forecast from a deep learning model and perform what-if analysis on the forecast.

Duration: 5:51
Posted: Jul 12, 2021

Probabilistic forecasting, i. e. estimating the probability distribution of a time series' future given its past, is a key enabler for optimizing business ...

Apr 21, 2017 · Pandas is a widely used Python library for data analysis and time series forecasting. It provides efficient and easy-to-use data structures ...

May 3, 2024 · The GluonTS Python package is a popular library for probabilistic time series forecasting. Because complex models require more complex data ...

Aug 28, 2020 · Kick-start your project with my new book Deep Learning for Time Series Forecasting, including step-by-step tutorials and the Python source code ...

Jun 12, 2019 · GluonTS simplifies the development of and experimentation with time series models for common tasks such as forecasting or anomaly detection.