This is a simple AI project that predicts whether a loan applicant is eligible for a loan or not. The project is implemented in Python and uses machine learning algorithms to make predictions based on various factors such as age, income, credit score, and loan amount.
To get started with the project, you will need to have Python installed on your system. You will also need to install the following libraries:
- Pandas
- NumPy
- Scikit-Learn
- Seaborn
- Matplotlib
You can install these libraries using pip, which is a package installer for Python. To install a library using pip, open a terminal or command prompt and type:
pip install pandas
pip install numPy
pip install scikit-learn
pip install seaborn
pip install matplotlib
To use the project, simply run the Python script. The script will prompt you to enter various details about the loan applicant such as age, income, credit score, and loan amount. Based on these details, the script will make a prediction about whether the applicant is eligible for a loan or not.
The project uses a machine learning algorithms called Logistic Regression, Svm and Decision Tree to make predictions. The algorithm is trained on a dataset of loan applicants with known eligibility status. The dataset is preprocessed to remove any missing values and to scale the features to a common range.
After training the algorithm, the model is used to make predictions on new loan applicants. The accuracy of the model is evaluated using a confusion matrix, which shows the number of true positives, true negatives, falsepositives, and false negatives.
If you would like to contribute to the project, feel free to fork the repository and submit a pull request. Please make sure to follow the coding standards used in the project and include appropriate documentation with your changes.
This project is licensed under the MIT License - see the LICENSE.md file for details.