- This is an end-to-end machine learning project built with Python that aims to predict the auction sale price of a bulldozer.
- Matplotlib was used for data visualization.
- Pandas was used for data preprocessing (dealing with missing data, parsing dates, and converting categorical data into numbers).
- Scikit-Learn's RandomForestRegressor was used during modeling and achieved a root mean squared log error of 0.25 after hyperparameter tuning.
- Check out the project here.
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srpineda/ml-project-bulldozer-saleprice-timeseries-regression
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An end-to-end machine learning project that aims to predict the auction sale price of a bulldozer. This is a time series regression problem.
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