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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
Last synced: 10 days ago
JSON representation
Linear regression model to predict the price of houses in Ames, Iowa based on 79 explanatory variables.
- Host: GitHub
- URL: https://github.com/mxsaad/house-price-predictor
- Owner: mxsaad
- License: mit
- Created: 2023-03-15T20:14:50.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2023-10-07T04:34:37.000Z (about 1 year ago)
- Last Synced: 2024-10-12T04:22:40.207Z (about 1 month ago)
- Topics: jupyter-notebook, kaggle-competition, linear-regression, machine-learning
- Language: Jupyter Notebook
- Homepage: https://github.com/mxsaad/house-price-predictor/blob/main/model.ipynb
- Size: 1.34 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# 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).