|Project Name||Stars||Downloads||Repos Using This||Packages Using This||Most Recent Commit||Total Releases||Latest Release||Open Issues||License||Language|
|Neural_prophet||2,954||5 days ago||7||March 22, 2022||39||mit||Python|
|NeuralProphet: A simple forecasting package|
|Orbit||1,584||1||4 months ago||17||April 28, 2022||54||other||Python|
|A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.|
|Flow Forecast||1,447||7 days ago||93||gpl-3.0||Python|
|Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).|
|Forecast||1,031||189||147||a month ago||86||January 10, 2022||14||R|
|forecast package for R|
|Wrf||965||6 days ago||147||other||Fortran|
|The official repository for the Weather Research and Forecasting (WRF) model|
|Web Traffic Forecasting||552||5 years ago||12||Python|
|Kaggle | Web Traffic Forecasting 📈|
|Timetk||551||13||22||2 months ago||18||April 07, 2022||22||R|
|Time series analysis in the `tidyverse`|
|M4 Methods||539||3 years ago||10||R|
|Data, Benchmarks, and methods submitted to the M4 forecasting competition|
|Modeltime||452||11||16 days ago||20||June 01, 2022||47||other||R|
|Modeltime unlocks time series forecast models and machine learning in one framework|
|Pyaf||425||4||a month ago||12||May 14, 2022||12||bsd-3-clause||Python|
|PyAF is an Open Source Python library for Automatic Time Series Forecasting built on top of popular pydata modules.|
We request that all new users of WRF please register. This allows us to better determine how to support and develop the model. Please register using this form:https://www2.mmm.ucar.edu/wrf/users/download/wrf-regist.php.
For an overview of the WRF modeling system, along with information regarding downloads, user support, documentation, publications, and additional resources, please see the WRF Model Users' Web Site: https://www2.mmm.ucar.edu/wrf/users/.
Information regarding WRF Model citations (including a DOI) can be found here: https://www2.mmm.ucar.edu/wrf/users/citing_wrf.html.
The WRF Model is open-source code in the public domain, and its use is unrestricted. The name "WRF", however, is a registered trademark of the University Corporation for Atmospheric Research. The WRF public domain notice and related information may be found here: https://www2.mmm.ucar.edu/wrf/users/public.html.