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https://github.com/mxsaad/house-price-predictor

Linear regression model to predict the price of houses in Ames, Iowa based on 79 explanatory variables.
https://github.com/mxsaad/house-price-predictor

jupyter-notebook kaggle-competition linear-regression machine-learning

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Linear regression model to predict the price of houses in Ames, Iowa based on 79 explanatory variables.

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# House Price Predictor

## Project Overview

This repository contains the code for a House Price Predictor, a Python-based project that predicts house prices with 87% accuracy. It utilizes linear regression and handles incomplete data effectively.

## Tech Stack

- **Python**: The project is developed in Python.
- **NumPy**: Used for numerical computations.
- **Matplotlib**: Used for data visualization.
- **Seaborn**: Used for advanced data visualization.
- **Pandas**: Used for data manipulation.

## Getting Started

To run the House Price Predictor locally:

1. Clone this repository to your local machine.

2. Navigate to the project directory.

3. Install required Python libraries:

```bash
pip install numpy matplotlib seaborn pandas scikit-learn
```

4. Run the predictor script:

```bash
python house_price_predictor.py
```

## Contributing

Contributions are welcome; please follow standard Git and GitHub contribution workflows.

## License

This project is licensed under the [MIT License](LICENSE).