Summary

Text sentiment is a benchmark of emotion that is measured from a text that has been made by someone. In general, there are two types of sentiment classification, namely positive which is a good emotion, and negative which is a bad emotion. Through NLP the sentiment classification of a text can be known automatically so that later it can be used quickly for various things later, for example measuring the level of credibility of something. In this portfolio, I will showcase the results of my own work in creating a web-based Indonesian Sentiment Text classifier using the transfer learning method using the BERT model and deployment using flask. 

All code results can be access on my GitHub repository: 

https://github.com/bintangfjulio/text_sentiment_analysis.git