The prupose of this project is to thoroughly analyze the potential dataset attributes that are useful in predicting the price of a used car. The dataset has around 400K records ahd 25 attributes. This project aims at visualizing the dataset attributes and find correlation between them. Furthermore, regression models: Linear Regresison, Ridge, Lasso Regression, KNeighborsRegressor, RandomForestRegressor, XGBRegressor have been implemented to predict the price of used cars. The base evaluation metircs is R2_score and Residual Plots are used for visualizing the model results.
Dataset Link: https://www.kaggle.com/austinreese/craigslist-carstrucks-data