Bag$-$of$-$Words $($BoW$)$ or CountVectorizer describes the presence of words within the text data. This process gives a result of one if present in the sentence and zero if absent$.$ This model therefore, creates a bag of words with a document$-$matrix count in each text document.

from sklearn.feature$\_$extraction.text import CountVectorizer