  Sentiment analysis of reviews is a popular task in natural language
processing. In this work, the goal is to predict the score of food reviews on a
scale of 1 to 5 with two recurrent neural networks that are carefully tuned. As
for baseline, we train a simple RNN for classification. Then we extend the
baseline to GRU. In addition, we present two different methods to deal with
highly skewed data, which is a common problem for reviews. Models are evaluated
using accuracies.
