Blue Book for Bulldozer Price Prediction – Machine Learning with Jupyter Notebook

A data science project to predict the sale prices of bulldozers using historical sales data and machine learning techniques in Jupyter Notebook.

Project Highlights:

• Analyze and clean bulldozer sales data for model training and evaluation.
• Feature engineering and preprocessing to extract meaningful insights from raw data.
• Build and tune regression models (including Random Forests) to predict sale prices.
• Visualize data distributions and model performance with plots generated in Jupyter Notebook.
• End-to-end reproducible workflow: from data loading to final predictions and submission.
• Uses widely adopted Python data science libraries: pandas, numpy, scikit-learn, and matplotlib.