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Abstract: A lot of research is already Focused on detecting the Fake news. A lot of things read online, especially in the social media feeds, which may appear to be true, often is not. Fake news is news, stories or mislead or deceive readers. Usually, the Fake news on social media and various other media is spreading and creates serious concern, these stories are created to either influence people’s views, or cause confusion and can often be a profitable business for online publishers. The spread of fake news in today’s digital world has effected beyond a specific group. Mixing both believable and unbelievable information on social media has made the difficulty of truth. That is, the truth will be hardly classified. This paper comes up with the applications of NLP (Natural Language Processing) techniques for the process will result in feature extraction and vectorization using a skit learn we build tfidf vectorization 'fake news', which is the misguiding news that is being published through unknown sources usually through social media due to its ability to cause a lot of social with destructive impacts.