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[Music] hi in this lecture well transform tokens into features and the first way to do that is bag-of-words lets count occurrences of a particular in our text the motivation is the following we are actually looking for marker words like excellent or disappointed and we want to detect those words and make decisions based on absence or a presence of that particular word and how it might work lets take an example of three reviews like good movie not a good movie didnt like and lets take all the possible words or tokens that we have in our documents and for each such lets introduce a new feature or column that will correspond to that particular word so that is a pretty huge matrix of numbers and how we translate our text into a vector in that matrix or row in that matrix so lets take for example good movie review we have the word good which is present in our text so we put one in the column that corresponds to that word then comes word movie and we put one in the second
