https://github.com/webdevcaptain/bulldozer-price-prediction
https://github.com/webdevcaptain/bulldozer-price-prediction
Last synced: 3 months ago
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- Host: GitHub
- URL: https://github.com/webdevcaptain/bulldozer-price-prediction
- Owner: WebDevCaptain
- License: mit
- Created: 2025-01-29T08:50:18.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-01-29T08:56:07.000Z (5 months ago)
- Last Synced: 2025-01-29T09:38:53.831Z (5 months ago)
- Language: Jupyter Notebook
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
- License: LICENSE
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README
## Bluebook for Bulldozers
The goal of this project is to build a machine learning model to predict the price of bulldozers. The data is from the [Kaggle Bluebook for Bulldozers](https://www.kaggle.com/c/bluebook-for-bulldozers/data) competition.
> Problem Category: `Regression`
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## Project Structure
1. [Modelling Experiments](./bluebook_for_bulldozers.ipynb)
2. [Exploratory Data Analysis](./eda.ipynb)
3. [Downloading the data](./download_dataset.ipynb)
---
## Libraries used:
- [Pandas](https://pandas.pydata.org/): For data manipulation and analysis.
- [NumPy](https://numpy.org/): For numerical operations.
- [Matplotlib](https://matplotlib.org/): For data visualization.
- [Scikit-learn](https://scikit-learn.org/): For machine learning algorithms.
Additional tools:
- [JupyterLab](https://jupyter.org/): For interactive notebook environment.
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## Extension:
In future, I will try to use `XGBoost` or `CatBoost` for better performance.
---
## LICENSE
This project is released under the [MIT License](LICENSE).