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Fake News Detection using Machine Learning is a comprehensive project that utilizes machine learning and natural language processing techniques to identify and classify fake news articles. The project includes data analysis, model training, and a real-time web application for detecting fake news.
Detect Real or Fake News. To build a model to accurately classify a piece of news as REAL or FAKE. Using sklearn, build a TfidfVectorizer on the provided dataset. Then, initialize a PassiveAggressive Classifier and fit the model. In the end, the accuracy score and the confusion matrix tell us how well our model fares.
CheckThis is a Fake News Detection website developed by Jonathan Lee as part of the Final Year Project (FYP). The aim of this project is to create a simple web application to help ease the process of verifying the validity of a news article online