In an era dominated by the rapid spread of information, distinguishing between genuine and fake news has become a critical challenge. This project leverages cutting-edge machine learning algorithms and text processing techniques to tackle this issue effectively.
Fake News Detection App is an intuitive tool designed to classify news articles as either Real or Fake with high accuracy. It empowers users to validate the authenticity of the information they consume, promoting awareness and combating misinformation.
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Text-Based Classification:
Users can paste the text of a news article into the app, which is then analyzed and classified in real-time. -
OCR Integration for Images:
Upload an image of a news article or screenshot, and the app extracts text using Optical Character Recognition (OCR) and performs classification. -
Interactive User Interface:
The app provides a clean, responsive, and user-friendly interface powered by Streamlit, ensuring ease of use for all users. -
Confidence Levels:
The app not only provides a classification (Real or Fake) but also displays the confidence level of its prediction.
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Machine Learning Algorithms:
A trained Logistic Regression model for high-accuracy text classification. -
NLP Techniques:
Utilizes TF-IDF vectorization for feature extraction from text data. -
Optical Character Recognition (OCR):
Integrated with pytesseract to extract text from uploaded images seamlessly. -
Streamlit Framework:
Enables the creation of a visually appealing and interactive web app. -
Joblib for Model Serialization:
Ensures efficient storage and loading of the trained model and vectorizer.
- Step 1: Clone the repository in your device:
git clone <repository_url>
cd <repository_directory>
- Step 2: Set up a virtual python environment:
python -m venv env
source .env\Scripts\activate
- Step 3: Install the required Python libraries:
pip install -r requirements.txt
- Step 4: Run the Flask/Streamlit application:
Streamlit: python app.py or, click here
Flask: python flaskapp.py