https://github.com/suvroneel/spam-email-classifier

It’s an E2E ML project to filter spam msgs by using naive bayes classifier ✨💖
https://github.com/suvroneel/spam-email-classifier

google-sheets-api machine-learning multinomial-naive-bayes naive-bayes-classifier natural-language-processing pandas python3

Last synced: 7 months ago
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It’s an E2E ML project to filter spam msgs by using naive bayes classifier ✨💖

• Host: GitHub
• URL: https://github.com/suvroneel/spam-email-classifier
• Owner: Suvroneel
• Created: 2024-01-25T16:32:49.000Z (about 2 years ago)
• Default Branch: Version-2.1.0
• Last Pushed: 2025-08-05T06:32:38.000Z (7 months ago)
• Last Synced: 2025-08-05T08:37:33.442Z (7 months ago)
• Topics: google-sheets-api, machine-learning, multinomial-naive-bayes, naive-bayes-classifier, natural-language-processing, pandas, python3
• Language: Jupyter Notebook
• Homepage: https://spam-email-and-sms-classifier-xghzt3pj3bvd5ltzqp6rs8.streamlit.app/
• Size: 3.1 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

README

          
🌟Spam Email Classifier | End-to-End ML Pipeline:


![Image](https://github.com/user-attachments/assets/439129bc-b593-4926-9faa-0d5fe90c7e57)

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 🚀  Tech Stack











          

          

          

                  



 Streamlit/Google Sheets API


Key Features:

✅ Text Preprocessing: 

📌**Lowercasing, tokenization, special char removal, stemming**

![Image](https://github.com/user-attachments/assets/ec0fa2e2-74ae-4002-9b42-b36d17f02930)

✅ Advanced NLP: TF-IDF vectorization + Multinomial Naïve Bayes

✅ Visual EDA: 

📌**Spam Word Cloud**

![Image](https://github.com/user-attachments/assets/197f20ed-fe33-4267-b060-551b21fdacef)

📌**Ham Word Cloud**

![Image](https://github.com/user-attachments/assets/96ca117e-85f1-4c41-ac03-2eb909f5e688)

✅ MLOps Ready: Pickle model serialization and scikit-learn pipelines

✅ Live Deployment: Streamlit web app + Google Sheets integration for user input tracking

Business Value:

🛡️ Spam Filtering: Blocks 99% of unwanted messages

📈 Data Collection: Logs predictions for model improvement

![Image](https://github.com/user-attachments/assets/4807df2a-7687-42a1-b4a0-aa972b17a490)

🔮 Scalable: Pipeline adapts to new spam patterns

🚧 Future Improvements

1. Deep Learning Upgrade

:construction: CNN Integration:

Implement character-level CNN models (e.g., Char-CNN) for context-aware spam detection

Compare performance against current TF-IDF + Naïve Bayes pipeline

Updates

=======================================================

📍Update 1 - Now user's input data and their respective output will be recorded and will be used for futher training and testings ✔✔

📍Update 2 - Minor fixes . Implemented speeling check for further checking ✔✔

📍Update 3 - The model is much more trained and a navbar along with a breath taking wallpaper is added