Machine Learning Model and Report Generation

This repository contains scripts to build a machine learning model for predicting loan risk based on financial data and generate a PDF report with model performance metrics and visualizations.

Table of Contents

• Prerequisites
• Installation
• File Structure
• Author
• License

Prerequisites

• Python 3.x
• Required Python packages: pandas, scikit-learn, matplotlib, seaborn

Installation

Clone the repository

git clone https://github.com/Asim-Sidd02/RiskPredectionSystem.git
cd RiskPredectionSystem

Install the dependencies using pip:

pip install pandas scikit-learn matplotlib seaborn

File Structure

The project directory structure is organized as follows:

• modelBuilding.py: Python script responsible for preprocessing the data, training a Random Forest Classifier, and evaluating its performance.

• main.py: Python script responsible for generating a PDF report (ML_Model_Report.pdf) with model performance metrics and visualizations.

• german_credit_data.csv: Dataset file used for training the machine learning model.

• ML_Model_Report.pdf: PDF report generated by main.py containing visualizations and metrics of the trained model.

Author

• Asim Siddiqui
• Contact Information
  • Email: asimsiddiqui8181@gmail.com
  • LinkedIn: Asim Siddiqui
  • Portfolio: Asim Sidd

License

This project is licensed under the MIT License. See the LICENSE file for details.