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Final Year Fake News Detection using Machine learning Project with Report, PPT, Code, Research Paper, Documents and Video Explanation.
Final Year Fake News Detection using Machine learning Project with Report, PPT, Code, Research Paper, Documents and Video Explanation.
Develop a machine learning program to identify when a news source may be producing fake news. We aim to use a corpus of labeled real and fake new articles to build a classifier that can make decisions about information based on the content from the corpus.
Fake News Detection with Machine Learning. Overview. What You'll Learn. In this section, you'll learn. How to use various scikit-learn machine learning algorithms....
Fake News Detector. This fake news detection system utilizes the following tools and frameworks: Streamlit | Joblib | Natural Language Toolkit (NLTK) | Scikit-learn | Beautiful Soup | Pandas | Regex. Explore the Fake News Detection system: Visit the Streamlit App View on GitHub.
Welcome to our Fake News Detection Project, where we embark on a journey to build a robust system that can determine the authenticity of news articles. In a world inundated with information, the ability to distinguish between real and fake news is crucial.
For our solution we will be using BERT model to develop Fake News or Real News Classification Solution. We achieved an accuracy of 95+ % on test set, and a remarkable AUC by a standalone BERT...
