🟢 This project aims to classify bank clients into two groups, good payers and bad payers, in order to approve or deny credit.
🟢 This was an extra project in Alura's Applied Data Science Bootcamp. The data was adapted by Alura from this Kaggle problem.
🟢 After analysing the data and arriving at a finished dataset, we began our machine learning part of the project. This can be found at this Jupyter Notebook.
🟢 Finally, we took our finished machine learning model and used in a Streamlit application which can be found here.
For the future:
- Improve the Machine Learning model;
- Improve the dataset analysis;
- Improve the Streamlit app.
Feel free to contact me for any tips or suggestions! 👋