Dinan Jayasinghe completed Machine Learning for Automotive

Built an end-to-end used-car pricing analysis for VW and Audi listings in the UK market. Combined the datasets, engineered predictive features such as car age and mileage-per-year, trained and compared Linear Regression and Random Forest models, and used R²/MAE/RMSE to show the Random Forest as the stronger pricing model. Also produced a business summary that identified the main pricing drivers and recommended deployment for CPO valuation workflows.

• Leakage-Free Feature Engineering
• Comparative Model Evaluation
• Business Translation of ML Results