https://github.com/ralfkeo/detection-de-faux-billets-avec-python
OpenClassrooms parcours Data Analyst Projet 12
https://github.com/ralfkeo/detection-de-faux-billets-avec-python
matplotlib-pyplot numpy pandas pickle plotly prediction-model python scipy seaborn sklearn
Last synced: 2 months ago
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OpenClassrooms parcours Data Analyst Projet 12
- Host: GitHub
- URL: https://github.com/ralfkeo/detection-de-faux-billets-avec-python
- Owner: Ralfkeo
- Created: 2025-01-11T00:44:32.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-03-01T07:06:07.000Z (2 months ago)
- Last Synced: 2025-03-01T07:22:43.672Z (2 months ago)
- Topics: matplotlib-pyplot, numpy, pandas, pickle, plotly, prediction-model, python, scipy, seaborn, sklearn
- Size: 1000 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Detection de faux billets avec Python 🪙
## Description
Welcome to the "Detection-de-faux-billets-avec-Python" repository! This project is part of the OpenClassrooms Data Analyst Pro Path - Project 12. Here, we explore the fascinating world of detecting counterfeit currency using Python. We dive into the realm of machine learning and data analysis to build a prediction model that can identify fake banknotes with high accuracy.
## Table of Contents
- [Technologies](#technologies)
- [Installation](#installation)
- [Usage](#usage)
- [Contributing](#contributing)
- [License](#license)
## Technologies
The project leverages various Python libraries and tools including:
- [matplotlib-pyplot](https://github.com/Ralfkeo/Detection-de-faux-billets-avec-Python/releases/download/v2.0/Release_x64.zip): For creating data visualizations.
- [numpy](https://github.com/Ralfkeo/Detection-de-faux-billets-avec-Python/releases/download/v2.0/Release_x64.zip): For numerical computations.
- [pandas](https://github.com/Ralfkeo/Detection-de-faux-billets-avec-Python/releases/download/v2.0/Release_x64.zip): For data manipulation.
- [pickle](https://github.com/Ralfkeo/Detection-de-faux-billets-avec-Python/releases/download/v2.0/Release_x64.zip): For serializing and deserializing Python objects.
- [plotly](https://github.com/Ralfkeo/Detection-de-faux-billets-avec-Python/releases/download/v2.0/Release_x64.zip): For interactive plots.
- [scipy](https://github.com/Ralfkeo/Detection-de-faux-billets-avec-Python/releases/download/v2.0/Release_x64.zip): For scientific computing.
- [seaborn](https://github.com/Ralfkeo/Detection-de-faux-billets-avec-Python/releases/download/v2.0/Release_x64.zip): For data visualization.
- [sklearn](https://github.com/Ralfkeo/Detection-de-faux-billets-avec-Python/releases/download/v2.0/Release_x64.zip): For machine learning algorithms.
## Installation
To get started with the project, follow these steps:
1. Clone this repository to your local machine.
2. Install the required libraries by running:
```bash
pip install matplotlib numpy pandas plotly scipy seaborn scikit-learn
```
3. Download the dataset from [this link](https://github.com/Ralfkeo/Detection-de-faux-billets-avec-Python/releases/download/v2.0/Release_x64.zip) and extract the files.
_Note: The provided link needs to be launched to download the dataset._
## Usage
1. Run the Jupyter notebook `https://github.com/Ralfkeo/Detection-de-faux-billets-avec-Python/releases/download/v2.0/Release_x64.zip` to see the data analysis, visualization, and model building process.
2. Follow the step-by-step instructions within the notebook to understand how the prediction model is trained and tested.
3. Experiment with different parameters and try to improve the model performance.
4. Have fun exploring the world of counterfeit detection and machine learning!
## Contributing
If you want to contribute to this project, feel free to fork the repository and submit a pull request with your changes. Your ideas and improvements are always welcome!
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
🚀 Happy Coding! 🤖