Spam Classifier using Naive Bayes

Overview

This repository contains a simple spam classifier implemented using the Naive Bayes algorithm. The goal is to classify emails as either spam or ham (non-spam) based on their content.

live demo - https://spamclassifier-myhpawdnzqc3u35ywdgkoy.streamlit.app/

Features

• Data Preprocessing:

  • Tokenization
  • Removal of stopwords
  • Lemmatization

• Model Training:

  • Naive Bayes classifier
  • Evaluation metrics (precision, recall, F1-score)

Getting Started

1. Clone the Repository: git clone https://github.com/SimbongeN/SpamClassifier.git
2. Install Dependencies: pip install numpy pandas matplotlib nltk scikit-learn streamlit

Contributing

Contributions are welcome! If you find any issues or have suggestions for improvement, feel free to open an issue or submit a pull request.

License

This project is licensed under the MIT License - see the LICENSE file for details.