Application of RNN for customer review sentiment analysis

In my previous blog post I wrote about using BeautifulSoup for scraping over two thousand Flixbus customer reviews and identifying company's strengths and weaknesses by performing NLP analysis. Building up on previous story, I decided to use the collected text data to train a Recurrent Neural Network model for predicting customers' sentiment, which proved to be highly efficient scoring 95.93% accuracy on the test set. Without any further ado let's jump into implementation. As a starting point, I loaded a csv file containing 1,780 customer reviews in English with the corresponding rating on the scale from 1 to 5, where 1 is the lowest (negative) and 5 is the highest (positive) rating. Now we have the data to work with.