This project aims to classify news as either real or fake using machine learning algorithms. It uses a dataset of news articles that have been labeled as either real or fake, and implements various machine learning algorithms to train models that can accurately predict the veracity of new unseen news articles.
- Download the dataset: MEGA Link
- Run Preprocessing.ipynb first.
- Run Visualization.ipynb (optional) and Models.ipynb.
- Run Prediction.ipynb.
- Python3
Our fake news detection system is based on machine learning models trained on a dataset of news articles. The accuracy of the system is dependent on the veracity and quality of the dataset used to train the model. Therefore, the system's ability to detect fake news may be limited by the accuracy and reliability of the dataset. Our system is intended to assist users in evaluating the credibility of news articles but should not be solely relied upon to make decisions. Users should exercise their own judgment when evaluating the accuracy and reliability of news articles.