The Loan Risk Classification project focuses on predicting the risk associated with loan applications using machine learning techniques. The goal is to classify loan applications into categories such as 'Approved' or 'Declined' based on various input features.
The repository is organized as follows:
loan_risk_classification.ipynb: Jupyter Notebook for interactive data exploration, preprocessing, model training, and evaluation.Assignment_Train.csv: CSV file containing the training dataset.Assignment_Test.csv: CSV file containing the test dataset.
loan_risk_classification.py: Main Python script for data processing, model training, evaluation, and saving.loan_risk_classification_report.pdf: A comprehensive report summarizing model performance and insights.model.h5: The trained model saved in HDF5 format.predictions.csv: Predictions made by the model on the test dataset.
To run this project, ensure you have the following Python libraries installed. You can install them using pip:
pip install pandas numpy matplotlib seaborn scikit-learn tensorflow jupyter