I developed a regression model to predict selling prices for used cars in the UK with a target Mean Absolute Percentage Error (MAPE) under 10%.

After validating and cleaning the data, I uncovered key non-linear relationships—such as a positive link between price and year, and a negative one with mileage.

I used standardization, cross-validation, and trained both Linear Regression and Decision Tree models to assess performance.

The project’s recommendations include automating price estimation for new listings, flagging mispriced vehicles, and enhancing dynamic pricing strategies and inventory planning.

👉 Check out the full notebook here

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