Now users can:

✅ Enter house details,

✅ Click Predict,

✅ Get AI-generated price estimates

⭐ Extra Features to Add

Beginner Level:

✅ Price Prediction,

✅ Clean UI,

✅ Charts

Intermediate Level:

✅ Location-based pricing,

✅ Property comparison,

✅ Download reports

Advanced Level:

✅ Map integration,

✅ Multiple ML models,

✅ AI recommendations,

✅ Real estate analytics dashboard

📂 Project Structure

house-price-prediction/
│
├── data/
├── models/
├── notebooks/
├── screenshots/
├── app.py
├── train.py
├── requirements.txt
├── README.md
└── house_data.csv

💼 Resume Project Description

House Price Prediction App

Developed an end-to-end Machine Learning application using Python, Pandas, Scikit-learn, and Streamlit to predict real estate prices based on property features. Performed data preprocessing, model training, evaluation, and deployed an interactive web application for real-time predictions.

🎯 Mini Challenge

Before moving to the next project, try these improvements:

1. Add Location as a feature

2. Compare Linear Regression vs Random Forest

3. Display prediction confidence

4. Deploy the app online

5. Upload the project to GitHub with screenshots and documentation

🔥 Double Tap ❤️ For Part-2