In recent years, as our social media has become more and more prevalent. The news websites and blogs have become into the limelight, there are number of web pages and social media that have come into the state that claim to report on upcoming events, but whose reliability has been brought up into question. Now the debate over such websites and news agencies has become so prevalent that the issue of ‘fake news’ is itself an vital part of the news world. What establishes `fake news,` in any case, has just turned out to be less clear as the topic has turned out to be increasingly normal, with standard news sources. Nowadays` fake news is making various issues from mocking articles to a created news and plan government publicity in certain outlets. fake news and absence of trust in the media are developing issues with immense consequences in our general public. It is needed to look into how the techniques in the fields of computer science using machine learning, natural language processing helps us to detect fake news. Fake news is now viewed as one of the greatest threats to democracy, journalism, and freedom of expression. In this research a comprehensive way of detecting fake news using machine learning model has been presented that is trained by two different data which is based on US election fake news and recent Indian political fake news respectively.

Machine Learning, Fake News, Data Cleaning, Classification Model, Text processing, Natural Language Toolkit

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