A Django & React application that forecast time series data using ARIMA and RNN models

Time-series-forecasting-ARIMA-RNN

Our paper | Time Series Forecasting


Description

ARIMA (Autoregressive Integrated Moving Average)

RNN (Recurrent neural network)

A Seasonal Time Series Data

User

  • Sign up, Sign in
  • Import Time series data (CSV)
  • Apply ARIMA, RNN
  • Forecast

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Technologies

  • Django-rest framework
  • React framework
  • PostgreSQL (Optional)

Features used

  • TensorFlow
  • Pandas
  • Keras
  • NumPy
  • Joblib
  • Knox
  • Material UI
  • Plotly js

How To Use

Back-end

Installation

cd .\server\
pip install -r requirements.txt

Package model changes

python manage.py makemigrations

Execute the changes into the database

python manage.py migrate

Run the server

python manage.py runserver

Front-end

Installation

cd .\Client\
npm install

Run the server

npm start

Demo

Time series Demo


License

MIT License

Copyright (c) [2022] [Khiati Walid]

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the “Software”), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.


Author Info

GitHub

View Github