Sentiment analysis is one of the most widely used tasks in NLP. An LSTM network can be used to classify short texts into desired categories, a classification problem. For example, a set of tweets can be categorized as either positive or negative. In this section, we will see such an example.
The implemented LSTM network will have three layers: an embedding layer, an RNN layer, and a softmax layer. A high-level view of this can be seen in the following diagram. Here, I summarize the functionalities of all of the layers: