Fake-News-Detection-using-Machine-Learning-

Built a machine learning model to classify news articles as real or fake using NLP techniques like tokenization, stopword removal, and TF-IDF. Trained Naïve Bayes and Logistic Regression models, achieving X% accuracy. Analyzed linguistic patterns to differentiate fake and real news.

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Python
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📰 Fake News Detection using Machine Learning

This project uses Natural Language Processing (NLP) and machine learning to classify news articles as real or fake.

📌 Project Overview

  • Preprocess and clean text data
  • Extract features using TF-IDF
  • Train and evaluate ML models (Naive Bayes, Logistic Regression)

🚀 How to Run

git clone https://github.com/yourusername/FakeNewsDetection.git
cd FakeNewsDetection
pip install -r requirements.txt
python main.py

🔧 Technologies Used

  • Python
  • Scikit-learn
  • NLTK
  • Pandas
  • TF-IDF

📂 Folder Structure

  • src/ contains all Python modules
  • data/ holds dataset
  • notebooks/ contains exploratory analysis