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.
- Python
- Streamlit
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
andham
messages in thedata
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.
-
GitHub: @Micky
-
LinkedIn: Michael Tamirie
Contributions, issues, and feature requests are welcome!
Feel free to check the issues page.
Give a ⭐️ if you like this project!
- Special thanks to CampusX youtube channel