Fake News Detection

Designed and developed a machine learning-powered web application to detect fake news, leveraging Passive Aggressive (89% accuracy) and Naive Bayes (93% accuracy) classifiers trained on a Kaggle dataset. Integrated the ML models seamlessly with a Python Flask backend for smooth and efficient predictions.

Built a minimal, responsive UI for real-time testing of news articles, enabling quick and accurate determination of authenticity.