A data-driven project predicting used car prices through EDA and a Linear Regression model. Insights revealed strong effects of year, mileage, and engine size on price. Achieving an R² of 0.83, the study highlights how adding categorical features can further refine predictions and boost model performance.
☆42Sep 23, 2025Updated last year
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