Linear Regression on USA Housing Dataset

This project applies linear regression to the USA Housing dataset.

Files in this Repository

• linear-regression.ipynb: This Jupyter notebook contains the code for the linear regression model.
• USA_Housing.csv: This is the dataset used in this project. It contains information about housing in various regions in the USA.

How to Run the Notebook

1. Ensure you have Jupyter installed. If not, you can install it by running pip install jupyter.
2. Navigate to the project directory and run jupyter notebook.
3. Open linear-regression.ipynb in the Jupyter notebook interface that appears in your web browser.

Dependencies

This project uses the following Python libraries:

• pandas
• numpy
• matplotlib
• seaborn
• scikit-learn

You can install any missing dependencies with pip install -r requirements.txt.

Results

The results of the linear regression model are visualized in the Jupyter notebook.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.