A modern Machine Learning + Flask web application that classifies email or SMS messages as Spam or Ham using TF-IDF and Naive Bayes.

This project is beginner-friendly, explainable, and perfect for learning NLP, ML model deployment, and portfolio showcase.

• ✅ Spam vs Ham email/SMS classification
• 🧠 Machine Learning model (Naive Bayes + TF-IDF)
• 🌐 Interactive Flask web application
• 🎨 Modern, responsive UI
• 📦 Model persistence using joblib
• 👤 About Developer button (LinkedIn integration)

• Python
• Flask
• Scikit-learn
• Pandas
• Joblib
• HTML & CSS

spam-email-classifier/
│
├── app.py
├── spam_email_model.joblib
├── tfidf_vectorizer.joblib
│
├── templates/
│   └── index.html
│
└── static/

The model is trained using a labeled spam email dataset from Kaggle:

• Columns
  • email_text → Content of the email/SMS
  • label → spam / ham

Dataset path used in Kaggle:

/kaggle/input/spam-email-classification-dataset/email_spam_dataset.csv

pip install flask scikit-learn pandas joblib

python app.py

http://127.0.0.1:5000

Spam

Congratulations! You won a cash prize. Click now to claim.

Ham

Hi, our meeting is scheduled for tomorrow at 11 AM.

Nayon Ahmed
🔗 LinkedIn: https://www.linkedin.com/in/nayonahmed/

• NLP beginners
• Machine Learning practice project
• Flask deployment demo
• Resume / portfolio project

If you find this project useful, feel free to ⭐ the repository!