Bag of Words model is the technique of pre-processing the text by converting it into a number/vector format, which keeps a count of the total occurrences of most frequently used words in the document. This model is mainly visualized using a table, which contains the count of words corresponding to the word itself. In other words, it can be explained as a method to extract features from text documents and use these features for training machine learning algorithms