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This project implements a supervised machine learning model to predict house prices using a linear regression approach. Leveraging a dataset with features such as area, number of bedrooms, bathrooms, and additional amenities, the model is trained to provide accurate price predictions.
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Project Completed with EDA Feature Ebginnering and Making a streamlit app
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