News is one of the most significant mediums for getting information and updates from across the world. Some people’s daily routines involve reading news for at least 10 minutes to stay current on world affairs, technology, entertainment, real estate prices, natural disasters, and so much more. News has a strong impact on people’s minds, therefore it is critical that the news that is being published in newspapers or on the web is authentic. Fake news provides incorrect facts and is a big concern owing to the power and influence it has on people. That is why detecting fake news is vital. It can have major effects on individuals and society, since misleading information can impact people’s opinions and decisions. Detecting this manually is impractical due to the millions of articles available on the web.

The goal of this project is to create a machine learning model using NLP techniques that will accurately detect whether a news article is true or fake. The types of models that will be used are Naive Bayes, Support Vector Machines, and some sort of ensemble learning. After the different types of models are created and analyzed the best model will be chosen.