🏦 CreditWise Loan Approval Prediction System

An end-to-end Machine Learning project that predicts whether a loan application should be Approved or Rejected.

📌 Project Overview

This project automates loan approval prediction using Machine Learning.

🎯 Problem Statement

Predict whether a loan should be Approved or Rejected using applicant information.

📂 Dataset Features

• Applicant Income
• Coapplicant Income
• Employment Status
• Age
• Marital Status
• Dependents
• Credit Score
• Existing Loans
• DTI Ratio
• Savings
• Collateral Value
• Loan Amount
• Loan Term
• Loan Purpose
• Property Area
• Education Level
• Gender
• Employer Category

Target: Loan_Approved (1 = Approved, 0 = Rejected)

⚙️ Technologies Used

• Python
• Pandas
• NumPy
• Matplotlib
• Seaborn
• Scikit-learn
• Jupyter Notebook

🚀 ML Pipeline

• Data Cleaning
• EDA
• Feature Engineering
• Label Encoding
• One-Hot Encoding
• Feature Scaling
• Train-Test Split
• Logistic Regression
• KNN
• Gaussian Naive Bayes
• Model Evaluation

📁 Project Structure

CreditWise-Loan-Approval-System/
├── CreditWise_Loan_Approval_Prediction.ipynb
├── loan_approval_data.csv
├── README.md
├── requirements.txt
└── images/

💻 Installation

pip install -r requirements.txt
jupyter notebook

📈 Future Improvements

• Random Forest
• XGBoost
• Streamlit Deployment

👨‍💻 Author

Aniket Kharose

GitHub: https://github.com/aniketkharose

LinkedIn: https://linkedin.com/in/aniket-kharose-3287242a5