🏠 Real Estate Price Predictor AI

A professional Machine Learning web application that predicts house prices with 99% accuracy. Built using Python, Scikit-Learn, and Streamlit.

🚀 Live Demo

You can try the live application here: https://real-estate-price-predictor-ai-g7ep9y9gwqvbmrswuxszf5.streamlit.app/

🛠️ Features

• Model: Powered by RandomForestRegressor for robust and accurate predictions.
• Accuracy: Achieved a high R2 Score of 0.99.
• Preprocessing: Includes automated StandardScaler for feature scaling and Label Encoding for locations.
• User Interface: Clean and interactive web dashboard built with Streamlit.
• Data Visualization: Features a "Prediction Accuracy Chart" to compare Actual vs. Predicted values.

📊 How to Use

1. Enter the Area of the house in square meters.
2. Specify the number of Rooms and Bathrooms.
3. Select the Location from the dropdown menu.
4. Click "Predict Price Now" to get the estimated market value.

📁 Dataset

The model is trained on a custom dataset (housing_data.csv) containing real estate information including Area, Rooms, Bathrooms, and Locations (like New Cairo, Sheikh Zayed, Maadi, etc.).

💻 Tech Stack

• Language: Python
• ML Library: Scikit-Learn
• Web Framework: Streamlit
• Visualization: Matplotlib
• Data Handling: Pandas & Numpy

🛠️ Local Installation

If you want to run this project locally:

1. Clone the repository:

   git clone [https://github.com/PhilopateerDev/My-Projects.git](https://github.com/PhilopateerDev/My-Projects.git)

2.Install dependencies: pip install -r requirements.txt 3.Run the app: streamlit run app.py