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hi text cleaning is one of the major activity in a natural language processing pipeline sometimes real world data is very messy that you will spend most of the time cleaning the text before making it ready and to be fed into the model so in this video we are going to see some andy methods and functions that you can use for cleaning nlp data now it will be a combination of custom written function and in some cases it will be packages that are ready to available hand to use in your nlp pipeline so lets get started so in this case what im going to do is im going to use the well-known data set fetch 20 news groups the 20 news groups data set is available as part of scikit-learn data set so im just importing from scikit-learn data sets import fetch 20 news cube 20 news group and then what im doing is im just taking the training data set out of it there is a test as well but im just going to use the training data set i am assigning it to newsgroup underscore train i am just importing