Treffer: GluonTS: Probabilistic and Neural Time Series Modeling in Python.

Title:
GluonTS: Probabilistic and Neural Time Series Modeling in Python.
Authors:
Alexandrov, Alexander1 alxale@amazon.com, Benidis, Konstantinos1 kbenidis@amazon.com, Bohlke-Schneider, Michael1 bohlkem@amazon.com, Flunkert, Valentin1 flunkert@amazon.com, Gasthaus, Jan1 gasthaus@amazon.com, Januschowski, Tim1 tjnsch@amazon.com, Maddix, Danielle C.1 dmmaddix@amazon.com, Rangapuram, Syama1 rangapur@amazon.com, Salinas, David1 dsalina@amazon.com, Schulz, Jasper1 schjaspe@amazon.com, Stella, Lorenzo1 stellalo@amazon.com, Türkmen, Ali Caner1 atturkm@amazon.com, Yuyang Wang1 yuyawang@amazon.com
Source:
Journal of Machine Learning Research. 2020, Issue 78-118, p1-6. 6p.
Database:
Business Source Elite

Weitere Informationen

We introduce the Gluon Time Series Toolkit (GluonTS), a Python library for deep learning based time series modeling for ubiquitous tasks, such as forecasting and anomaly detection. GluonTS simplifies the time series modeling pipeline by providing the necessary components and tools for quick model development, efficient experimentation and evaluation. In addition, it contains reference implementations of state-of-the-art time series models that enable simple benchmarking of new algorithms. [ABSTRACT FROM AUTHOR]

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