Monzer

Fake News Detection

Developed a high-accuracy fake news detection system using Ensemble and SVM classifiers. Preprocessed large datasets with NLTK and Pandas, applying TF-IDF and CountVectorizer for feature extraction. Leveraged PyTorch and scikit-learn to build and evaluate models, achieving 98.88% accuracy with LinearSVC and 98.65% with Random Forest Ensemble. The system maintained precision, recall, and F1-scores above 98%, showcasing the role of machine learning in combating political misinformation.

• Python,
• PyTorch,
• scikitLearn,
• Pandas