This repository showcases the use of a Regression model to predict the best price for the used and new cars. The data was provided by Cars45 as part of the company's recruitment exercise which I participated in. The data contains features typically used to purchase cars such as make, model, engine displacement, engine power, price (NGN) etc.
The repo focuses on the different segments of the task which I employed to reach my final predictions. These segments include:
- Data Cleaning
- Finding and Eliminating Extreme Values (Outliers)
- Handling Missing Values
- Feature Engineering and Selection
- Model Development and Cross-Validaion.