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

• Host: GitHub
• URL: https://github.com/97k/spam-ham-web-app
• Owner: 97k
• License: mit
• Created: 2018-08-29T18:46:38.000Z (about 6 years ago)
• Default Branch: master
• Last Pushed: 2018-10-02T12:22:41.000Z (about 6 years ago)
• Last Synced: 2024-04-20T12:43:57.191Z (7 months ago)
• Topics: 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
• Language: Jupyter Notebook
• Homepage: https://spamham.herokuapp.com/
• Size: 68.3 MB
• Stars: 29
• Watchers: 4
• Forks: 12
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# 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/)