Update README.md

README.md

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 ## Coding Challenge - Deep Learning for NLP (Foong)
 
 ### Description:
-This repository contains notebook using scikit-learn SVM to classify real & fake news.
+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
@@ -9,7 +9,7 @@ Libraries used: Scikit-learn, NLTK, pandas, numpy, csv
 ### Write-up:
 The accuracy of the model is 0.995. 
 
-There are a couple 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 most commonly used words which should be removed as features. Tehrefore, more data cleaning should be eprformed prior to model building.
-- Try using neural network by setting batch size, apply dropout & finetuning it
-- Run cross validation
+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