Update README.md

Author: YuHengKit

README.md

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 # NLP
 ```Sentimental Analysis & Prediction -Twitter.ipynb``` is using default Twitter dataset in ntlk and use Naive Bayes Classifier as Classifier and obtain 99.6% accuracy. Reference: https://www.digitalocean.com/community/tutorials/how-to-perform-sentiment-analysis-in-python-3-using-the-natural-language-toolkit-nltk
 
-```Sentimental Analysis - LSTM.ipynb``` is using Stanford sentiment treebank data and use LSTM as Classifier and able to detect sarscam. Reference: https://towardsdatascience.com/sentiment-analysis-for-text-with-deep-learning-2f0a0c6472b5
+```Sentimental Analysis - LSTM.ipynb``` is using <a> href=https://nlp.stanford.edu/sentiment/code.html Stanford sentiment treebank data </a> and use LSTM as Classifier and able to detect sarscam. Reference: https://towardsdatascience.com/sentiment-analysis-for-text-with-deep-learning-2f0a0c6472b5