The objective of this project is to create a machine learning model/estimator that can forecast the selling price of bulldozers using factors such as their production date, dimensions, model, and other relevant attributes.
- Python 3
- Jupyter Notebook
- Scikit-learn
- Pandas
- NumPy
- Matplotlib
- Clone the repository.
git clone https://github.com/iamharshvardhan/Bulldozer-SalePrice-Regressor.git
- Open the
end-to-end-bulldozer-price-regression.ipynb
Jupyter Notebook. - Run the cells in the notebook to train and evaluate the machine-learning model.
The machine learning model (RandomForestRegressor
) achieves the score of "0.45174586332956956" on Root_Mean_Square_Log_Error
metric.
This project is licensed under the MIT License
.