Loan Approval Prediction

This is a full-stack web application designed to predict the likelihood of loan approval based on user data. The project consists of a Python backend that serves a machine learning model and a React frontend for the user interface.

Project Structure

• frontend/: Contains the React application built with Vite and Tailwind CSS.
• backend/: Contains the backend API built with Python (likely Flask or FastAPI) which runs the machine learning model.

Getting Started

Prerequisites

• Node.js (for the frontend)
• Python 3.8+ (for the backend)

Backend Setup

1. Navigate to the backend directory:

   cd backend

2. Install the dependencies:

   pip install -r requirements.txt

3. Start the backend server:

   python app.py

   The backend typically runs on port 5000 (Flask default).

Frontend Setup

1. Open a new terminal and navigate to the frontend directory:

   cd frontend

2. Install the dependencies:

   npm install

3. Start the development server:

   npm run dev

   The frontend will start on http://localhost:5173 by default.

Usage

Once both the frontend and backend servers are running, open your browser and navigate to the frontend URL (e.g., http://localhost:5173). Fill out the required details in the form to get an instant loan approval prediction.

Technologies Used

• Frontend: React, Vite, Tailwind CSS, Lucide React (for icons)
• Backend: Python, Machine Learning Model