Fake News Detection
A Step-by-Step Guide : - Fake news has become a significant problem in today's digital world, where misinformation spreads rapidly. In this project, we built a Fake News Detection System using Machine Learning (ML) and Natural Language Processing (NLP) to classify news articles as Fake News or Real News. This project uses Python, scikit-learn, and NLP techniques to: * Process and clean news data * Convert text into numerical features using TF-IDF (Term Frequency-Inverse Document Frequency) * Train a Logistic Regression model to classify Fake vs. Real news * Provide a user-friendly web interface (Streamlit) * Announce results via Text-to-Speech (TTS) for better accessibility Project Components 1.Dataset (fake_news_dataset.csv) → Contains real and fake news headlines 2.Text Preprocessing → Removing stopwords and special characters 3.F-IDF Transformation → Converting text into numerical data 4.Machine Learning Model → Logistic Regression for classification 5.Web App (Str...
