Markdown# 📊 AI Intelligence Dashboard

A professional, containerized Flask application for customer churn prediction using Scikit-Learn, Pandas, and Tailwind CSS.

🚀 Live Demo

Project URL: https://ai-intelligence-dashboard.onrender.com/

🛠 Project Setup

Before running the app locally, ensure your environment is ready:

1. Environment Variables: Create a .env file in the root directory.
2. Add Credentials:

   MYSQL_ROOT_PASSWORD=your_password
   MYSQL_PASSWORD=your_password 
   
   

3. Data: Ensure customer_data.csv is inside the /data folder.

🚀 Docker Commands

Use these commands to manage the application: • Start the App: docker-compose up --build • Stop Services: docker-compose down • Train the AI Model: docker-compose run --rm web python model_trainer.py

📦 Deployment (Render)

This project is configured for easy deployment on Render:

1. Push your latest changes to GitHub.
2. Log in to Render.com and create a new Web Service.
3. Connect your GitHub repository.
4. Select Docker as the Runtime.
5. Add your Environment Variables (MYSQL credentials) in the Render 'Environment' tab.
6. Render will automatically build and deploy your container.

🌳 Git Branching Workflow

Always work on a feature branch to keep the main branch stable:

1. Create branch: git checkout -b feature/your-task-name
2. Save progress: git add . then git commit -m "Description of changes"
3. Push to GitHub: git push origin feature/your-task-name

© 2026 Daniel Tzul