---
slug: ml-loan
title: Machine Learning for Loan Prediction
type: Academic Project
description: Predicting loan approval and default risk using machine learning classification techniques.
shortDescription: A project applying machine learning to predict loan approvals and assess default risk.
publishedAt: 2025-01-24
readingTime: 2
status: Completed
tags:
  - Python
  - Machine Learning
  - Regression
  - Finance
  - Data Science
icon: i-ph-money-wavy-duotone
---

This project focuses on building machine learning models to predict loan approval outcomes and assess default risk. The objective is to develop robust classification models that identify creditworthy applicants.

## 📊 Project Objectives

- Build and compare multiple classification models for loan prediction
- Identify key factors influencing loan approval decisions
- Evaluate model performance using appropriate metrics
- Optimize model parameters for better predictive accuracy

## 🔍 Methodology

The study employs a range of machine learning approaches:

- **Exploratory Data Analysis (EDA)** - Understanding applicant characteristics and patterns
- **Feature Engineering** - Creating meaningful features from raw data
- **Model Comparison** - Testing multiple algorithms (Logistic Regression, Random Forest, Gradient Boosting, etc.)
- **Hyperparameter Tuning** - Optimizing model performance
- **Cross-validation** - Ensuring robust generalization

## 📄 Detailed Report

<iframe src="/projects/loan-ml.pdf" width="100%" height="1000px">
</iframe>
