Fake news refers to the fabricated information which is spread to the general public mostly via the Internet-based media platforms. This project uses the concept of Natural Language Processing (NLP) and ML concept of Supervised learning to build the fake news detection model. A comparison among the ML classification algorithms (Logistic Regression, Passive-aggressive classification, Stochastic Gradient Descent and Decision Tree) is made based on the accuracy, to mark the best model.
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View Code? Open in Web Editor NEWA NLP based ML model for fake news detection