Spam emails are a major issue in email communication, clogging inboxes and posing security threats. The Spam Email Classifier project aims to automate the identification of spam emails using the Naive Bayes algorithm and Natural Language Processing (NLP) techniques. This project processes email content through NLP steps like tokenization, stopword removal, and stemming to extract features. The Naive Bayes classifier then uses these features to predict whether an email is spam or ham (non-spam) based on the likelihood of specific word occurrences. By leveraging the simplicity and effectiveness of Naive Bayes, this model provides a fast and accurate solution for detecting spam emails, enhancing email management and security.
- 🚀 Real-time email classification with high accuracy.
- 🔍 NLP-powered text preprocessing for feature extraction.
- 📊 Supports multiple input formats (
.txt,.csv,.eml). - 🔧 Easily customizable machine learning models.
- 🌟 Interactive and user-friendly interface.
- Programming Language: Python
- Libraries: Scikit-learn, Pandas, NumPy, Matplotlib, NLTK , Seaborn
- ML Algorithms: Naive Bayes
- Deployment: Streamlit for a lightweight, interactive interface
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Clone this repository:
📂 Copy the repository to your local machine:
git clone https://github.com/<your-username>/<repository-name>.git
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Navigate to the project folder:
🛠 Move into the project directory:
cd <repository-name>
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Install dependencies:
📦 Install the required Python packages:
pip install -r requirements.txt
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Run the app:
▶️ Start the Streamlit app:streamlit run app.py
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Open in your browser:
🌐 The app will open automatically at http://localhost:8501.
🎉 Enjoy using the app and detecting spam with ease!😊
https://amanraj-creator-spam-email-detection-system-spamdetector-iufy1k.streamlit.app/
Feel free to fork this repository and submit pull requests!
This project is licensed under the MIT License
- Inspired by real-world spam detection challenges
- Special thanks to the open-source community for libraries and tools
Made with ❤️ by AMAN RAJ