Credit_Card_Approvals

Build an ML-based credit card approval predictor for commercial banks to automate application analysis, saving time and reducing errors. High loan balances, low income, or excessive credit inquiries often lead to rejections. This project replicates real banks' automation for efficient, accurate, and faster decision-making.

The dataset used in this project is the Credit Card Approval dataset from the UCI Machine Learning Repository. and Project is Assigned by DataCamp

Project Tasks That I Covered:

1. Credit card applications
2. Inspecting the applications
3. Splitting the dataset into train and test sets
4. Handling the missing values (part i)
5. Handling the missing values (part ii)
6. Handling the missing values (part iii)
7. Preprocessing the data (part i)
8. Preprocessing the data (part ii)
9. Fitting a logistic regression model to the train set
10. Making predictions and evaluating performance
11. Grid searching and making the model perform better
12. Finding the best-performing model