This file contains a description of what is done in the project. It consists to predict car prices using the CarPrice.csv dataset from Kaggle and the linear regression model from scikit learn
The data was loaded and processed by checking the null values, the duplicates and the outliers.
The feature engineering consisted to split the data (features and label) into 80 percent of train and 20 percent for test. the features were normalize.