Note
This project was completed for Mathematics of Computing 2 at RMIT University.
Warning
This repository has already been archived and is intended solely for academic purposes. We accept no responsibility for any issues that may arise from using our project and do not condone any behavior that violates academic integrity.
This repository focus on predicting the satisfaction level of airplane passengers. It includes sections on dataset source, details, variables, and the response variable, along with goals and objectives of the analysis. We use Jupyter Notebook to detail data cleaning, preprocessing, and visualization techniques. The dataset is an Airline Passenger Satisfaction dataset from Kaggle, and it is structured for predictive modeling in customer satisfaction. Our notebook includes various analyses and visualizations to understand and predict passenger satisfaction levels.
This project is licensed under the MIT. This means that you are free to use, modify, and distribute the project under the terms of this license.
- Weixi Guan (Chrisio Gwaan) - @ChrisioGwaan
- Pak Yin Lai (Marco Lai) - @Marcolai0905
The intent of this license is to allow for the free use of this project for educational, research, and personal projects. However, please adhere to the following guidelines:
- Academic Integrity: This project should not be used for purposes that violate academic integrity policies of educational institutions.
- Commercial Use: If you intend to use this project for commercial purposes, please check the specific terms of the license or contact the authors.
- Liability: The authors are not responsible for any damages or issues arising from the use of this project.
For more details on the license, please refer to the LICENSE file in this repository.