Loan Approval Prediction

Inspiration

I was inspired to do this project to learn and improve my machine-learning in python skills

What it does

It is an ML model written in python to predict the loan approval status for a given data.

How we built it

I built it using the Loan Predication dataset from Kaggle. (https://www.kaggle.com/datasets/ninzaami/loan-predication) I used python libraries such as Pandas, Numpy, Sklearn, and Seaborn.

Challenges we ran into

The dataset has to be preprocessed to remove null values and prepare it for the model. I first tried using a Random Forest Regressor but it resulted in very poor accuracy. Then I tried using SVM which gave reasonably good accuracy

Accomplishments that we're proud of

What we learned

I learned how to preprocess data and use SVM to create an ML model.

What's next for Loan Approval Prediction

I would work on improving the accuracy and using different datasets.

Built With

• pandas
• python
• sklearn