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https://github.com/97k/spam-ham-web-app

A web app that classifies text as a spam or ham. I am using my own ML algorithm in the backend, Code to that can be found under machine_learning_section. For Live Demo: Checkout this link
https://github.com/97k/spam-ham-web-app

bag-of-words data-visualization django heroku-deployment jupyter-notebook machine-learning machine-learning-projects multinomial-naive-bayes nlp nltk spam-classification text-classification tfidf

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A web app that classifies text as a spam or ham. I am using my own ML algorithm in the backend, Code to that can be found under machine_learning_section. For Live Demo: Checkout this link

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# SpamHam
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](https://github.com/aditya98ak/spam-ham-web-app/blob/master/machine_learning_section/SpamHam.ipynb) 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](https://spamham.herokuapp.com)

### Built With

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

### Installing/ Things you need to install the Web App and how to set up the project locally?

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

#### Steps
- 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](https://github.com/aditya98ak/spam-ham-web-app.git)
- pip install -r requirements.txt
- Run the app using python manage.py runserver

### Milestones for version 2
- 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 :heart: by
**Aditya Kaushik** - [linkedin.com/adityakaushik001](https://www.linkedin.com/in/adityakaushik01/)