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 # **NEWS CLASSIFIER**
 
+[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/) 
+[![forthebadge](https://forthebadge.com/images/badges/built-with-love.svg)](https://forthebadge.com)
+[![forthebadge](https://forthebadge.com/images/badges/open-source.svg)](https://forthebadge.com)
+
 ### **PROJECT ID: 06**
->## ✍  PROJECT DESCRIPTION
-To develop and ML application to help users get notified about dubious news sources using natural language processing.
+>##   PROJECT DESCRIPTION
+**To develop and ML application to help users get notified about dubious news sources using Natural Language Processing**.
+
+![Image of Web Application](https://github.com/khushboogupta13/NEWS-CLASSIFIER/blob/master/Fake%20News%20Prediction.jpeg)
 
->## 📂  TECHNOLOGY USED
+>##   TECHNOLOGY USED
 
-* Flask
-* Sklearn
+1. [Python](https://www.python.org/) (several of its libraries like [scikit-learn](https://scikit-learn.org/stable/), [nltk](https://www.nltk.org/), [matplotlib](https://matplotlib.org/), [numpy](https://numpy.org/) and [pandas](https://pandas.pydata.org/)) for building the model.
+2. [HTML](https://developer.mozilla.org/en-US/docs/Web/HTML), [CSS](https://developer.mozilla.org/en-US/docs/Learn/CSS), [Javascript](https://www.javascript.com/) for building the front end of the web application.
+3. [Flask](https://flask.palletsprojects.com/en/1.1.x/) for the backend of the web application.
 
->## 💻  GETTING STARTED
+>##   TO RUN THE MODEL ON LOCAL DEVICE
 
 => **Fork <a href=https://github.com/LetsUpgrade/NEWS-CLASSIFIER><img src="https://img.icons8.com/ios/24/000000/code-fork.png"></a>this repository to start contributing.**
 
@@ -18,4 +25,26 @@ To develop and ML application to help users get notified about dubious news sour
     1) git init -initializes the git repository from the GitHub. 
     2) git clone -Clone the repository to your local machine
       (git clone https://github.com/<your-github-username>/LetsUpgrade/NEWS-CLASSIFIER.git)
-```    
+```   
+
+>## &nbsp; BUILDING OF THE MODEL
+1. **Dataset**: https://www.kaggle.com/c/fake-news/data?select=train.csv
+2. **Algorithm Used**: [Multinomial Naive Bayes](https://scikit-learn.org/stable/modules/generated/sklearn.naive_bayes.MultinomialNB.html#:~:text=The%20multinomial%20Naive%20Bayes%20classifier,tf%2Didf%20may%20also%20work.)
+
+
+>## &nbsp; FUTURE IMPROVEMENTS
+
+1. Making a **chrome plugin** for the web application.
+2. Further improving the accuracy of the model.
+3. Training the model further on more datasets.
+
+>## &nbsp; REFERENCES
+1. [Fake News Classifier I](https://medium.com/swlh/build-your-own-fake-news-classifier-7918f05c2ec7)
+2. [Fake News Classifier II](https://towardsdatascience.com/building-a-fake-news-classifier-using-natural-language-processing-83d911b237e1)
+
+>## &nbsp; LICENSE
+
+All rights reserved. Licensed under the MIT License.
+
+[![GitHub license](https://img.shields.io/github/license/Naereen/StrapDown.js.svg)](https://github.com/Naereen/StrapDown.js/blob/master/LICENSE)
+
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