SpamHam is a text-classification app which detects whether the message/email is spam or not. I've used Naive-Bayes along with NLP (TF-IDF, Bag of Words and more).
In order to perform an experiment I've combined two datasets (Enron email spam/ham and SMS spam classification) into one to gather more data. See this notebook to get what I am saying.
To check out this project in action I've deployed it on heroku
Click on this link to check
- Django 2.1
- Python 3.6
- Scikit-Learn
- Numpy
- Pandas
- Matplotlib
- Seaborn
- HTML5
- CSS
- Bootstrap-v4
- Love
- Python3
- Pip
- Django(2.1)
- Conda
- Make a virtual environment using "conda create -n envname python=3.6 pip"
- source activate envname (for mac/linux) | activate envname (for windows)
- Download or clone this repo by git clone https://github.com/aditya98ak/spam-ham-web-app.git
- pip install -r requirements.txt
- Run the app using python manage.py runserver
- Implement login and tailor experience for each user
- Collect the result reported by user for false classification of messages/email
- Model will self-learn from the reported data
Made with ❤️ by Aditya Kaushik - linkedin.com/adityakaushik001