Monkey Pox Visualisation and Modeling Project

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Table of Contents

1. About The Project
   • Built With
2. Roadmap
• Data sourcing
• Preprocessing
• Feature engineering
• Visualizations
• Model training
• Model deployment
3. Getting Started
   • Prerequisites
   • Installation
4. Usage
5. Contributing
6. License
7. Contact
8. Acknowledgments

About The Project

Monkey Pox visualization project aims to provide the world with a continually updated visualization to follow with the trend of Monkey pox epidermics globally. It provides charts to follow the trend of monkey pox globally, by region or by country. The data is continuosly updated everyday to keep the charts and visualizations up to date. similar to our world in data The project also seeks to answer so basic and frequently asked questions about the epidermic such as:

• Country with the highest cases
• Country with the lowest cases
• Cases per region
• Region with the highest cases
• Region with the lowest cases
• Date of highest cases per Country
• Date of lower cases per Country and many other questions

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Going To Be Built With

• Python
• Pandas
• Matplotlib
• Seaborn
• Dash
• Streamlit
• sklearn
• panel

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Roadmap

• Data download (to download the data, just run python src/data/download_data.py)
• • Fix data downloads scheduler
• Preprocessing
• Feature engineering
• visualizations
• Model training
• Model deployments
  • Nested Feature

See the open issues for a full list of proposed features (and known issues).

Data

Data sources:

• globaldothealth
• globaldothealth-new-cases Here we will talk about the sources of the data and the script for sourcing the data

Preprocessing

Here we are going to talk about the preprocessing process

Feature engineering

We will talk about the various feature engineering techniques used.

Visualizations

Here will contain explanation of some charts and visualizations we created, techniques and tools used.

Model

Here we will talk about the models, the various models tried and thought into the types of models used.

Deployment

Here we will discuss the various technologies and techniques used to deploy the model.

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Usage

To use this product, it will be displayed in a url that will be attached here. However, it is still currently under production

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with a descriptive header to better communicate what the contribution is about. Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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License

Distributed under the MIT License. See LICENSE.txt for more information.

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Contact

• Ajala, Marvellous - @madeofajala - ajalaoluwamayowa00@gmail.com

Project Link: https://github.com/ajalamarvellous/monkey-pox-project

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Acknowledgments

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