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  “Verify Before You Trust — Let AI Detect the Truth.”

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  “Verified Information You Can Trust.”

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  “Spot Misinformation Before It Spreads.”

About the Project

💡 Inspiration

Fake news and misinformation spread rapidly through social media and online platforms. Many people read and share news without verifying whether it is genuine. We wanted to create a simple AI-powered solution that helps users identify potentially fake news quickly.

🛠️ What We Built

We developed an AI Fake News Detection System that analyzes a given news article or headline and predicts whether it is likely to be Real or Fake using machine learning.

The system provides a simple interface where users can enter news content and receive an instant prediction.

📚 What We Learned

Through this project, we learned how to:

• Prepare and process text data for machine learning.
• Use TF-IDF for text feature extraction.
• Train a machine learning classification model.
• Integrate the ML model with a Flask web application.
• Build a simple and user-friendly interface for AI-based prediction.

⚙️ How We Built It

The project was developed using Python, Flask, Scikit-learn, HTML, CSS, and JavaScript.

The basic workflow is:

News Input → Text Preprocessing → TF-IDF Feature Extraction → ML Model → Real/Fake Prediction

🚧 Challenges We Faced

One of our main challenges was converting unstructured news text into useful features for the machine learning model. We also had to connect the trained model with the web interface and make the prediction process simple for users.

🎯 Impact

Our goal is to encourage users to verify information before believing or sharing it. This project demonstrates how AI and machine learning can be used as a first-level tool to combat online misinformation.

“Detect the Fake. Trust the Facts.”

Built With

• artificial
• detection
• fake
• flask
• intelligence
• learning
• machine
• natural-language-processing
• news
• python
• scikit-learn
• tf-idf