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A simple machine learning project that predicts house prices based on square footage, number of bedrooms, and number of bathrooms using a Linear Regression model.”

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Implement a linear regression model to predict the prices of houses based on their square footage and the number of bedrooms and bathrooms.

Housing Price Prediction

This repository contains Python code for predicting house prices based on features such as area, number of bedrooms, and number of bathrooms. The code uses linear regression as the machine learning model and performs outlier analysis and treatment to improve the model's accuracy.

Requirements

Make sure you have the following libraries installed:

  • Python

pandas

scikit-learn

matplotlib

streamlit

You can install these libraries using pip:

pip install pandas matplotlib seaborn numpy scikit-learn

Features

Interactive dataset viewer.

Model performance metrics.

Visualization: Actual vs Predicted plot.

Custom input for house price prediction.

Dollar to Rupee conversion.

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A simple machine learning project that predicts house prices based on square footage, number of bedrooms, and number of bathrooms using a Linear Regression model.”

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