Assume 'data' includes the numeric features of cars

features $=$ data$[[\text{'}$Car$\_$Price', 'Car$\_$Mileage', 'Car$\_$Finance$\_$plan'$]].$ Using python and machine learning

$1.$ Build content$-$based recommender systems using various unsupervised learning algorithms, such as: Distance$/$Similarity measurements, K$-$means, Principal Component Analysis $($PCA$),$ etc.

$2.$ Build collaborative$-$filtering recommender systems using various supervised learning algorithms such as: K Nearest Neighbours, Neural Networks, Linear Regression, Logistic Regression, Random Forest, etc