Time-series-forecasting-ARIMA-RNN

Our paper | Time Series Forecasting

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Table of Contents

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

• Description
• Technologies
• How To Use
• Demo
• License
• Author Info

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Description

ARIMA (Autoregressive Integrated Moving Average)

• Source code

RNN (Recurrent neural network)

• Source code

A Seasonal Time Series Data

• CSV file

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

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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

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Front-end

Installation

cd .\Client\

npm install

Run the server

npm start

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Demo

Time series Demo

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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.

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Author Info

• LinkedIn - @KhiatiWalid
• LinkedIn - @HamrouneYoucef