Thenujan Arulnesan completed Machine Learning for Automotive

Built an end-to-end used-car pricing analysis for VW and Audi listings in the UK market. The work combined exploratory analysis, feature engineering, and model comparison, then used the tuned Random Forest’s strong R², MAE, and RMSE to support a pricing recommendation for a Certified Pre-Owned team. The submission also translated model outputs into business terms, including brand premium and portfolio risk.

• Exploratory Data Understanding
• Feature Engineering for Price Prediction
• Model Comparison and Metric Interpretation
• Business Translation of ML Results