Applying SVM for Fake News Identification

Project Overview

This project utilizes Support Vector Machines (SVM) to identify and classify fake news. It includes two main notebooks:

Machine Learning - Compared Models.ipynb: This notebook compares various machine learning models to determine the most effective one for fake news identification.
Machine Learning - SVM Model.ipynb: This notebook focuses on using the SVM model for the identification and classification of fake news.

The dataset used in this project includes news articles from various sources, which have been pre-labeled as "true" or "fake."

To run these notebooks, ensure you have the following dependencies installed in your environment:

pip install numpy pandas sklearn matplotlib

Name		Name	Last commit message	Last commit date
Latest commit History 8 Commits
Dataset.rar		Dataset.rar
Machine Learning - Compared Models.ipynb		Machine Learning - Compared Models.ipynb
Machine Learning - SVM Model.ipynb		Machine Learning - SVM Model.ipynb
README.MD		README.MD
stop_words.txt		stop_words.txt