In this project, we have a loan dataset from a bank. The data contain all the loans requested, whether the bank decided to grant it, whether the borrower managed to repay it, and the information about the borrower at the moment he/she is asking for the loan. The goal is to build a model to predict whether a customer will repay, which can be used to decide whether to grant loans to future customers.
Feature engineering, exploratory data analysis and visualization, as well as two solutions using a logistic regression and a random forest classifier are shown in loan_eda_modeling.ipynb. Based on the methods developed in loan_eda_modeling.ipynb, a pipeline using object-oriented programming is implemented in loan_oop.ipynb.