readme: ## Coding Challenge - Deep Learning for NLP (Foong)
  
  ### Description:
  This repository contains a Jupyter notebook using scikit-learn SVM to classify real & fake news.
  
  Dataset: https://www.kaggle.com/clmentbisaillon/fake-and-real-news-dataset
  Libraries used: Scikit-learn, NLTK, pandas, numpy, csv
  
  ### Write-up:
  The accuracy of the model is 0.995. 
  
  There are a couple of misclassified news articles and to improve the model's performance on these news articles, here're some suggestions:
  - Remove stop words: The news article title and text contain a lot of commonly used words which should be removed as features. Therefore, more data cleaning should be performed prior to model building.
  - Try using the neural network by setting batch size, apply dropout & finetuning it
  - Run cross-validation