Fake News Classifier

In this job, I collaborated with Chayma Bouzaidi

Table of contents

1. Overview
2. Requirements
3. Setting up the API
4. Start the App

Overview

In this project, we built an end to end fake news classifier. This starts from training a machine learning classifier to deploying a web app.😀

How to do 🤔?

First of all, let's have a look how the app looks like 🤓:

As you see, this web app allows a user to detect either an article is fake or real news. To do, the user just pastes the article in the text area and clicks on Predict.

NB : You can add some articles in the test dataset file : server/data/fake_or_real_news_testset.csv

To build this app, we followed this main steps:
       • Training a machine learning classifier (Logistic Regression)
       • Building an interactive web app using React.js
       • Setting a REST API using Flask

Requirements

       • Node.js (version 12.13.0)
       • Python (version 3.7.4)
       • Flask : pip install flask

Setting up the API

       • Go to server\ directory and run app.py script in order to start the API
       • You can get the pickle of our trained model from Dropbox: https://www.dropbox.com/s/r2bhfdvzb7rb99k/model.pkl?dl=0 and store it in server\model directory
NB : Keep in mind that when you first run the app.py script, the machine learning model (~350MB) will be loaded into your machine RAM

Start the App

       • Go to client\ directory and run npm install && npm start to start the App