Pavankumar Karsinapu completed Machine Learning for Automotive

Built an end-to-end used-car pricing workflow for VW and Audi listings: combined the datasets, performed exploratory analysis, engineered age-based and mileage-normalized features, and trained both Linear Regression and Random Forest models. The candidate evaluated the models with R² and MAE, found Random Forest to be materially stronger, and translated the results into a clear CPO pricing recommendation with human-in-the-loop safeguards.

• Leakage-Free Feature Engineering
• Model Comparison with Business Context
• Applied Metric Interpretation