Bulldozer Price Predictor: Project Overview

• Predicting the sale price of Bulldozers provided their attributes using Machine Learning.
• Created a regression model on time series data that predicts sale prices for bulldozers (RMSLE).
• Data was
• Optimized a Random Forest Regressor model using RandomizedSearchCV to achieve the most accurate model (lowest RMSLE).

Data & Problem

• Data Acquisition: Kaggle
• Problem:
• Sucess Metric:

Code and Resources Used

• Python Version: 3.9
• Environment: Miniconda, Jupyter Notebook
• Packages: Pandas, Scikit-Learn, NumPy, Matplotlib, Seaborn, Joblib

Data Preprocessing

EDA & Feature Engineering

Model Building

Model Performance

Feature Importance