This repository is for a machine learning model to predict whether a loan application will be approved or not based on several factors.
The dataset used for this project (loan_data.csv) is located in the same directory as the Jupyter notebook. It contains information on various factors that may affect a loan application, such as the applicant's income, credit history, and property location.
To run the Jupyter notebook, you will need to have the following libraries installed:
Pandas Numpy Matplotlib Seaborn Scikit-learn
After installing the required libraries, you can open the Jupyter notebook in your preferred environment and run the cells to load the dataset, preprocess the data, and train the model.
The final model can be used to predict whether a loan application will be approved or not by providing input values for the various factors.
The final model achieved an accuracy of 80% on the test set. The model was evaluated using a confusion matrix and classification report.
This project was created by Shubham.