Skip to content

NLP project to classify articles out of five classes: business, entertainment, politics, sport, tech

License

Notifications You must be signed in to change notification settings

EzzEddin/classicle

Repository files navigation

License

Classicle 📖

Classicle is a Natural Language Processing project that can classify your article out of five classes: business, entertainment, politics, sport, tech. It is read like classical and it is a portmanteau word -- a blend of classify and article.

Demo

Classicle demo is now on my youtube channel classicle_demo

How to use classicle

  1. Clone this project and cd into the classifybutton folder:
$ git clone https://github.com/EzzEddin/classicle.git
$ cd classicle
$ cd classifybutton
  1. Using python3, run the following:
$ python3 manage.py runserver 127.0.0.1:8002
  1. Go to the browser and write the server link, in the url, that you specified in the last command 127.0.0.1:8002
  2. The page you saw at the demo will apear so you can put your article in there to classify.

Setup

Install dependencies:

  • django
  • tensorflow
  • keras
  • pickle
  • numpy
  • csv
  • wget (optional)

How classicle works

Classicle is a project run on a django server just by clicking on classify button, it will run the python script which has the deep learning model.

Data

The data I used for training and testing is bbc-news articles available here.

Acknowledgements

The deployment and deep learning model in this project are inspired by Browser-based Models with TensorFlow.js course and Natural Language Processing in TensorFlow course while running the model written in python script by a click on a button at django server is inspired by this blog. I also want to thank my friend Nour for answering my questions whether in development or testing. Thank you, guru.

License

MIT, Copyright (C) 2020 by Ezz El Din Abdullah

About

NLP project to classify articles out of five classes: business, entertainment, politics, sport, tech

Topics

Resources

License

Stars

Watchers

Forks

Packages

No packages published