iamharshvardhan / Bulldozer-SalePrice-Regressor

The objective of this project is to create a machine learning model that can forecast the selling price of bulldozers using factors such as their production date, dimensions, model, and other relevant attributes.

Bulldozer-SalePrice-Regressor

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.

Prerequisites

• Python 3
• Jupyter Notebook
• Scikit-learn
• Pandas
• NumPy
• Matplotlib

Instructions

• 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.

Results

The machine learning model (RandomForestRegressor) achieves the score of "0.45174586332956956" on Root_Mean_Square_Log_Error metric.

License

This project is licensed under the MIT License.