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vikasgautam2003/Fake-or-Real-News-Classifier-Using-Naive-Bayes

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📰 Fake-or-Real News Classifier Using Naive Bayes

![Python](https://www.python.org/) ![Scikit-learn](https://scikit-learn.org/) ![Hugging Face](https://huggingface.co/vikasgautam2003/Fake-or-Real-News-Classifier-Using-Naive-Bayes)

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

🚀 Features

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

🛠️ Tech Stack

—Language → Python 3.10+
—Library → Scikit-learn (Naive Bayes, TF-IDF)
—Notebook → Jupyter for training and inference

📂 Project Structure

bash

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



⚙️ 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

👨‍💻 Author

Vikas Gautam