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

1. Django 2.1
2. Python 3.6
3. Scikit-Learn
4. Numpy
5. Pandas
6. Matplotlib
7. Seaborn
8. HTML5
9. CSS
10. Bootstrap-v4
11. Love

1. Python3
2. Pip
3. Django(2.1)
4. 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