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πŸ“° Fake-or-Real News Classifier Using Naive Bayes

Python Scikit-learn Hugging Face

⚑ An AI-powered Fake-or-Real News Classifier using Naive Bayes.
Classifies news articles as fake or real based on text features.


πŸš€ Features

βœ… Simple, lightweight Naive Bayes model
βœ… Works on CSV datasets of news articles
βœ… Preprocessing and training included in Jupyter Notebook
βœ… Easy to integrate in Python projects


πŸ› οΈ Tech Stack

  • Language β†’ Python 3.10+
  • Library β†’ Scikit-learn (Naive Bayes, TF-IDF)
  • Notebook β†’ Jupyter for training and inference

πŸ“‚ Project Structure

β”œβ”€β”€ Fake_Real_Data.csv          # Dataset
β”œβ”€β”€ NewClassificationModel.ipynb  # Notebook with training & inference
└── README_HD.md                # Hugging Face repo documentation



βš™οΈ Usage

Clone the repository:

git clone https://huggingface.co/vikasgautam2003/Fake-or-Real-News-Classifier-Using-Naive-Bayes
cd Fake-or-Real-News-Classifier-Using-Naive-Bayes


Install dependencies:

pip install scikit-learn pandas numpy


Open the Jupyter Notebook NewClassificationModel.ipynb to train or test the model.

🎯 Use Cases

Detect fake news articles in datasets or streams

Demonstrate Naive Bayes text classification in portfolio

Quick integration for educational purposes

πŸ‘¨β€πŸ’» Author

Vikas Gautam
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