Fake News Detection Using Deep Learning Models
This component focuses on detecting fake news articles through advanced Natural Language Processing (NLP) and deep learning techniques. The system was trained and evaluated using four models — SimpleRNN, LSTM, BiLSTM, and CNN — to compare performance in terms of accuracy, F1-score, and loss metrics.A Streamlit-based web interface was also developed for interactive testing, allowing users to input news text and instantly visualize the prediction results (real or fake).