Fake News Detection App

📝 Overview

Fake news has become a widespread issue in today's digital world. This project aims to detect fake news using machine learning techniques. The model classifies news articles as Fake or Real based on text analysis. The web interface, built using Streamlit, allows users to input news text and get predictions instantly.

📌 Features

  • 📰 Pandas for data processing
  • 🤖 Scikit-learn for machine learning (Logistic Regression)
  • 💾 Model serialization with joblib
  • 🌐 Web interface powered by Streamlit

🚀 Installation

📥 Clone the Repository 

git clone https://github.com/your-username/fake-news-detection.git
cd fake-news-detection

📦 Install Dependencies 

pip install -r requirements.txt

📊 Dataset

  • The model is trained using a dataset containing labeled fake and real news articles.
  • Preprocessing includes text vectorization using TF-IDF Vectorizer.

🏋️ Model Training

  • The dataset is preprocessed using Pandas.
  • Text features are extracted using TfidfVectorizer.
  • The model is trained using Logistic Regression.
  • The trained model is saved using joblib.

▶️ Running the Streamlit App 

streamlit run app.py

🛠️ Usage

  1. Enter a news article text in the input box.
  2. Click the Detect button.
  3. The model will classify the article as Real or Fake.

🎮 Live Demo

Check out the live demo of the app here: Fake News Detector

  • Deployed at Streamlit Community Cloud

📌 Dependencies 

# Required Libraries
Python 3.x
Pandas
Scikit-learn
Joblib
Streamlit

📜 License

This project is open-source under the MIT License.

💡 Feel free to contribute and improve this project!. If anyone know how to fetch real time data using api keys to get real time data 🚀