This project is an implementation of spam filtering using the Naive Bayes algorithm. The algorithm is trained on a dataset of spam and non-spam messages, and is then able to classify new messages as spam or not spam.
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.
- Python 3.6 or higher
- NumPy
- Pandas
- Scikit-learn
- Clone the repository:
git clone https://github.com/steve-cse/Spam-Filtering-BN.git
- Install the required packages:
pip install -r requirements.txt
This project is open for contributions. Feel free to fork the repository, make changes, and create a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.