Skip to content

In this repo I have done an end to end spam message classifier. In the website a user can pass the message and the model will predict whether the email is spam or ham. I have used a labeled data to train my model and streamlit for the UI and deployment.

Notifications You must be signed in to change notification settings

Micky373/spam_classifier

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

17 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Spam Message Classifier

In this repo I have done an end to end spam message classifier. In the website a user can pass the message and the model will predict whether the email is spam or ham. I have used a labeled data to train my model and streamlit for the UI and deployment.

The spam messages data contains more than 5000 labeled messages.

screenshot

Built With

  • Python
  • Streamlit

Live Demo

Live Demo Link

Getting Started Locally

git clone https://github.com/Micky373/spam_classifier.git

cd spam_classifier

pip install -r requirements.txt

streamlit run spam_classifier.py

Then go and on any browser put this link (http://localhost:8501/)

Then put a message in the box.

If you need there are some spam and ham messages in the data folder, you can pass those messages in the box and check.

Then the website will show you if the message is spam or ham.

More clear discription about how the recommendation system was built and the API fetching can be found in the notebooks folder.

Author

🤝 Contributing

Contributions, issues, and feature requests are welcome!

Feel free to check the issues page.

Show your support

Give a ⭐️ if you like this project!

Acknowledgments

About

In this repo I have done an end to end spam message classifier. In the website a user can pass the message and the model will predict whether the email is spam or ham. I have used a labeled data to train my model and streamlit for the UI and deployment.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published