Developer · 2024
Car Price Regression — AutoTrader ML
Applied machine-learning coursework using UK AutoTrader vehicle listing data to explore price modelling. Covers data preprocessing, feature engineering, EDA, and comparative regression models.
Overview
Applied machine-learning coursework project using UK AutoTrader vehicle listing data to explore price modelling and core ML principles. Contains a fully reproducible Jupyter notebook and an accompanying academic report covering data preprocessing, feature engineering, exploratory data analysis, and comparative regression models.
The question
Vehicle pricing involves many interacting features (mileage, age, brand, fuel type). Manual valuation is inconsistent and doesn't scale.
My approach
Built an end-to-end ML pipeline with preprocessing, feature engineering, and comparative evaluation of linear and tree-based regression models using standard metrics, with structured analysis of bias–variance trade-offs and validation strategy.
Outcome and limits
End-to-end ML pipeline with structured discussion of bias–variance trade-offs, scaling effects, and validation strategy.
Results are specific to the project setup and data; broader use would require additional evaluation.
Interested in this work? Get in touch.