📰 Fake News Detector

NOTE !!!

This app simply works on the training data I have used. It can not classify lates or live news ; to do that you can use web scraping and train on that data.!!!

Unmask the truth, one article at a time. https://fake-news-detector-using-ml-nddimension.streamlit.app/

In an age of viral misinformation, the Fake News Detector empowers you to verify news content with AI. Whether you're a journalist, researcher, or just a concerned reader — our model helps you distinguish between what's real and what's fake using machine learning.

Image Preview 🌟

Fake News

Real News

🚀 Why Fake News Detector?

"Misinformation can spread faster than truth." Fake News Detector uses NLP and logistic regression to analyze textual content and give a verdict in seconds.

🌠 Paste an article. ▲ Click a button. ✔️ Know the truth.

No browser plugins. No heavy tools. Just instant AI validation.

🌟 Workflow

🧠 How It Works

1. Preprocessing: Cleans and normalizes raw text using regex.

2. Feature Extraction: Converts text into numeric vectors with TF-IDF.

3. Model Prediction: A trained Logistic Regression model evaluates the text.

4. Verdict: The model outputs Real or Fake, based on learned patterns.

⚡ All under the hood with lightning-fast performance.

🧰 Features

Function	Description
🔍 Paste & Analyze	Paste full news articles directly in the app
✅ Real-time Results	Instantly receive prediction feedback
💾 Model Saving	Uses joblib to store trained models
📊 Metrics Output	View precision, recall, and F1-score
🌐 Streamlit UI	Intuitive and elegant web interface

📦 Requirements

pandas
scikit-learn
joblib
streamlit
Pillow

Install everything using:

pip install -r requirements.txt

⚙️ Getting Started

1. Clone the repository

git clone https://github.com/NDDimension/Fake-News-Detector-using-ML.git
cd fake-news-detector/CODE FILE

2. Download Dataset

https://drive.google.com/drive/folders/1uViefNaUP9xhgzR5O4xrAOWYJpuYBOjt

3. Execute

app.ipynb

4. Run the Fake News Detector

streamlit run frontend.py

5. Paste an article and get your result!

✨ Highlights

• ✅ Minimal setup — just paste and analyze

• ✅ Lightweight and fast ML pipeline

• ✅ Custom CSS and styled UI with Streamlit

• ✅ Easy to retrain with new data

🔮 What’s Coming

• 📌 Browser extension integration

• 🧠 Model upgrade to transformer-based classifiers (like BERT)

• 📱 Mobile-ready PWA version

• 🌍 Multi-language support

🧠 Powered by:

• scikit-learn
• Streamlit
• pandas
• joblib

📜 License

Licensed under the MIT License.

Fake News Detector — Let AI be your truth filter.