NewsGuard is a machine learning system built to detect fake or misleading news articles. By leveraging Natural Language Processing (NLP), it classifies text as Legitimate or Fake News, providing a confidence score and an explanation using LIME.
newsguard/
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├── datasets/ # Raw and cleaned data files
├── analysis/ # EDA reports and data visualizations
├── docs/ # Documentation, test results, and API usage
├── scripts/ # Python scripts (training, testing, LIME, etc.)
├── model/ # Saved models, vectorizers, and features
├── api/ # Flask API implementation
├── ui/ # (Optional) React front-end for user interaction
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├── README.md # Project overview and instructions
├── requirements.txt # Required Python libraries
├── .gitignore # Files/directories to ignore in version control
- Fake News Classifier using Naive Bayes & TF-IDF
- REST API with
/predictand/explainroutes - LIME Explainability for interpretable results
- Confidence score for predictions
- Clean documentation and test logs
- Tested with Postman + documented test outputs
- Python (NLP & API)
- Scikit-learn, LIME, Pandas
- Flask (Backend API)
- Postman (API testing)