Abstract: - With the popularity of mobile technology and social media growing, information is readily available. Mobile Appand social media platforms have overturned traditional media in the distribution of news. Alongside the incrementin the utilization of online media stages like Facebook, Twitter, and so forth news spread quickly among a large numberof clients with an extremely limited ability to focus time. Machine learning and Knowledge-based approach and approach are the two techniques utilized for investigating the truthiness of the content. Public and private assessments on a wide assortment of subjects are communicated and spread persistently through various online media. Most methodologies are utilized, for example, regulated AI. The spread of phony news has extensive results like the making of one-sided feelings to influencing political race results to support certain applicants. Additionally, spammers utilize engaging news features to produce income utilizing notices through click baits. In this paper, we intend to perform a parallel grouping of differentnews stories accessible online with the help of thoughts identifying with Artificial Intelligence, Natural Language Processing, and Machine Learning. The result of the project determines the fake news detection for social networks using machinelearning and also checks the authenticity of the publishing news website.Keywords: - Fake News, News articles, Internet, Social media, Classification, Artificial Intelligence, Machine Learning