i have finally completed my Car recommendation Project which takes some details about the cars you want and it will recommend that are most relevant to those choices.

I created a tags column after combining all the features of every car and converted it into vectors matrix and did the some on the input data then used the Cosine_similarity function from the scikit-learn library which compared the choices vector matrix to the existing ones in the dataset and gives a scores, when the score is higher then it is more relevant and vice versa. As output i have shown the top 5 most relevant cars.