VincentKervyn / classification-app

deploiment ML model on streamlit

ML Classification App

This is a Streamlit app displaying a 'dashboard' showing the analysis process to predict churn degree based on a dataset

Table of Contents

1. About The Project
   • Built With
2. Installation
3. Usage
4. Contributing
5. License
6. Contact

About The Project

During the course of my training with becode I created this app project

Built With

• Python 3.8.10

Installation

1. Clone the repo

   git clone https://github.com/VincentKervyn/classification-app.git

2. Install dependencies

   pip install -r requirements.txt

Usage

streamlit run streamlit.py

Or go to https://share.streamlit.io/vincentkervyn/classification-app/main/streamlit.py for the online version

Contributing

Any contributions you make are greatly appreciated.

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

License

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

Contact

Vincent Kervyn de Meerendré - [e-mail]