🏠 House Price Prediction using Streamlit 🌟 Features 🧩 Proposed a predictive model to estimate house prices based on various features. 🌐 Designed the model using Linear Regression for accurate price forecasting. 💻 Implemented a user-friendly Streamlit interface for an enhanced user experience. 📈 Delivered precise price predictions through a web-based application. 🛠 Tools/Technologies Programming Languages: Python Frameworks: Streamlit Libraries: Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn Tools: Jupyter Notebook, VS Code, Pickle, Joblib 📊 Model Performance Mean Squared Error (MSE): 0.78303