Project

Spam Filtering

Python
Streamlit
Keras
Tensorflow

Spam Filtering using Convolutional Neural Network (CNN)

Spam Filtering

Python Streamlit Keras scikit-learn Tensorflow Docker

Spam-filtering is a website based spam classifier that uses Deep Learning algorithm (Convolutional Neural Network) to classify whether a text is a spam or not.

Features💡

By using spam-filtering you can:

  • Checks whether a text is spam or ham.
Technology 👨‍💻

Spam-filtering is created using:

  • Python - Python as the main programming language.
  • Streamlit - Streamlit as the web framework.
  • Keras - Keras as the Deep Learning framework.
  • scikit-learn - scikit-learn as the Machine Learning framework.
  • Tensorflow - Tensorflow as the Deep Learning framework.
Structure 📂
spam-filtering
├── .github
├── .streamlit
├── docs
├── modules
├── pages
├── .gitignore
├── Dockerfile
├── Home.py
├── LICENSE
├── README.md
└── requirements.txt
  • .github is a folder that used to place Github related stuff like CI pipeline.
  • .streamlit is a folder that contains configuration files for streamlit.
  • docs contain documentation of this app.
  • modules is a folder that contains modules especially CNN and preprocessing.
  • pages is a folder that contains pages of this app.
  • .gitignore is a file to exclude some folders like venv.
  • Dockerfile is a file that contains all the commands to build an image.
  • Home.py is the main file and homepage of this app.
  • LICENSE is a file that contains the license we use in this app.
  • README.md is the file you are reading now.
  • requirements.txt is a file that contains a list of dependencies used in this app.
Installation 🛠️
docker pull putuwaw/spam-filtering
  • Run the downloaded image:
docker run -p 8501:8501 putuwaw/spam-filtering
  • Open web browser and visit:
0.0.0.0:8501
Contributors ✨


Putu Widyantara
Kenny Belle
Madya Santosa
Dheva Surya