House Price Prediction

An interactive web application that predicts house prices using a Random Forest regression model. Built with Python and Streamlit, this project allows users to input property features and receive instant price predictions.

Features

• Random Forest regression model trained on housing data
• User-friendly Streamlit interface for inputting property details
• Instant prediction of house prices based on input parameters
• Visualizations of data trends and model insights (if applicable)

Technologies Used

• Python 3.x
• scikit-learn
• Streamlit
• pandas, NumPy, matplotlib (for data processing and visualization)

Install necessary libraries : pip install streamlit pip install scikit-learn

Download .pkl file from House_Price_Prediction.ipynb and add it to project folder