https://github.com/blacksujit/fake-news-detection
This repository contains a machine learning model built to detect fake news articles. The project leverages natural language processing techniques and a supervised learning approach to classify news articles as either real or fake based on their content.
https://github.com/blacksujit/fake-news-detection
backend-api classification deployement developement fake-news-detection machine-learning model-development models pkl-model transformer-architecture unique-approach
Last synced: 2 months ago
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This repository contains a machine learning model built to detect fake news articles. The project leverages natural language processing techniques and a supervised learning approach to classify news articles as either real or fake based on their content.
- Host: GitHub
- URL: https://github.com/blacksujit/fake-news-detection
- Owner: Blacksujit
- Created: 2024-06-25T18:15:25.000Z (11 months ago)
- Default Branch: main
- Last Pushed: 2024-07-21T13:21:43.000Z (10 months ago)
- Last Synced: 2025-01-29T11:22:56.007Z (4 months ago)
- Topics: backend-api, classification, deployement, developement, fake-news-detection, machine-learning, model-development, models, pkl-model, transformer-architecture, unique-approach
- Language: Jupyter Notebook
- Homepage: https://fake-news-detection-chi.vercel.app
- Size: 205 MB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Fake News Detector
This project aims to detect fake news using machine learning. The project includes a Flask-based application that serves both backend (for model training and prediction) and frontend (for user interaction).
# Web Page :
## Folder Structure
- `run.py`: Main application file combining both frontend and backend.
- `model/`: Contains the trained model and script to train the model.
- `requirements.txt`: Dependencies for the project.
- `static/`: Static files (CSS, JS).
- `templates/`: HTML templates.
- `data/`: Folder containing the dataset.
## Dataset Information:
Download the dataset from [Kaggle Machine Learning](https://www.kaggle.com/datasets/emineyetm/fake-news-detection-datasets)
## Installation
1. Clone the repository.
```bash
git clone https://github.com/Blacksujit/Fake_News_Detection.git
```
2. Download a dataset suitable for fake news detection and place the file in the `data/` folder (e.g., `fakenews.csv`).
3. Virtual Environment setup
```bash
python -m venv venv
```
```bash
venv\Scripts\activate
```
3. Install the dependencies:
```bash
pip install -r requirements.txt
```
4. Run the application:
```bash
python run.py
```
6. Open your browser and go to `http://127.0.0.1:5000` to use the application.
## License
This project is licensed under the MIT License.