Commercial banks receive a lot of applications for credit cards. Many of them get rejected for many reasons, like high loan balances, low income levels, or too many inquiries on an individual's credit report, for example. Manually analyzing these applications is mundane, error-prone, and time-consuming. In this project, I try to build an automatic credit card approval predictor using machine learning techniques, just like the real banks do.

The dataset used in this project is the Credit Card Approval dataset from the UCI Machine Learning Repository.

Citation: Dua, D. and Graff, C. (2019). UCI Machine Learning Repository. Irvine, CA: University of California, School of Information and Computer Science.