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📰 Fake News Detection Web App

A professional-grade machine learning web application to detect fake news using NLP techniques and Streamlit. Built using the ISOT dataset.

🚀 Features

  • Detects whether news is Real or Fake
  • Built using multiple ML models (Logistic, Random Forest, Naive Bayes)
  • User-friendly UI with examples
  • Clean layout and responsive design
  • Preprocessing includes lemmatization, stopwords removal, vectorization
  • Multilingual support and language detection (optional upgrade in progress)

💻 Tech Stack

  • Python
  • Scikit-learn
  • Pandas, Numpy
  • Streamlit
  • Pickle
  • ISOT Dataset

📸 Screenshots

🏠 Home Page Home Page

🔍 Prediction Output Prediction Output

🔗 Live Demo: Click here to try the app

📂 Project Structure

├── app.py # Streamlit web app ├── models/ # Pretrained ML models + vectorizer │ ├── logistic_model.pkl │ ├── naive_bayes_model.pkl │ ├── random_forest_model.pkl │ ├── fake_news_detector.pkl │ └── vectorizer.pkl ├── assets/ # Screenshots for documentation │ ├── screenshot_home.png │ └── screenshot_prediction.png ├── data/ # Raw datasets (True.csv, Fake.csv) ├── requirements.txt # Required Python libraries └── README.md # Project overview

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🛠️ Tech Stack

  • Python 3.10
  • Streamlit (for UI)
  • scikit-learn (ML models)
  • NLTK / re (text preprocessing)
  • joblib (model serialization)

▶️ How to Run Locally

bash

1. Clone the repository

git clone https://github.com/a-kkuuu/Brainwave_Matrix_Intern-.git cd Brainwave_Matrix_Intern-

2. Install dependencies

pip install -r requirements.txt

3. Run the Streamlit app

streamlit run app.py

🧪 Example Click the “Generate Example” button in the app to auto-fill a real or fake news article sample and test prediction.

🏷 GitHub Topics streamlit · fake-news · machine-learning · logistic-regression · text-classification · scikit-learn

📬 Contact Developer: Akriti Kumari Email: [akriti91137@gmail.com] GitHub: https://github.com/a-kkuuu

🌟 Star This Repo! If you found this helpful or interesting, feel free to ⭐ star the repo to support the project!

✅ Next Steps

  1. Save this as README.md in your root folder.

  2. Run:

    bash git add README.md git commit -m "Final polished README with screenshots and details" git push Visit your GitHub repo and enjoy your professional-looking homepage! 😄