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Deep Learning for Time Series Forecasting

Project description

NeuralForecast: Deep Learning for Time Series Forecasting

[nikstla] (noun, nahuatl) Period of time.

CI codecov Python PyPi License: MIT

State-of-the-art time series forecasting for pytorch.

NeuralForecast is a python library for time series forecasting with deep learning. It provides dataset loading utilities, evaluation functions and pytorch implementations of state of the art deep learning forecasting models.


Here is a link to the documentation.


Stable version

This code is a work in progress, any contributions or issues are welcome on GitHub at:

You can install the released version of NeuralForecast from the Python package index with:

pip install neuralforecast

(Installing inside a python virtualenvironment or a conda environment is recommended.)

Development version in development mode

If you want to make some modifications to the code and see the effects in real time (without reinstalling), follow the steps below:

git clone
cd neuralforecast
pip install -e .

Current available models


This project is licensed under the MIT License - see the LICENSE file for details.

How to contribute


How to cite

If you use NeuralForecast in a scientific publication, we encourage you to add the following references to the related papers:

  author  = {XXXX},
  title   = {{NeuralForecast: Deep Learning for Time Series Forecasting}},
  journal = {arXiv preprint arXiv:XXX.XXX},
  year    = {2022}

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