AgboolaMubarak/Car-Price-Prediction

I developed 6 models that predicts the prices of cars in Nigeria based on independent variables like model, car type, color, location, distance travelled # Car-Price-Prediction In this project, I aimed to predict car prices based on a dataset containing 7205 rows of valuable information, including location, model, type, distance, color, and year. I implemented six different regression models to find the most accurate predictor. After thorough analysis, we found that the Decision Tree regression model outperformed the others, achieving a Root Mean Square Error (RMSE) of 0.95. This suggests that the Decision Tree model is our dataset's most reliable choice for predicting car prices. This project demonstrates the power of regression modeling in predicting car prices and highlights the significance of choosing the correct algorithm for the task at hand. I hope our findings and codebase can be a valuable resource for anyone interested in similar predictive modeling tasks.