In this section, we are going to focus on the general deep learning architectures that can be used for sentiment analysis. The following figure shows the processing steps that are required for building the sentiment analysis model.
So, first off, we are going to deal with natural human language:
Figure 1: A general pipeline for sentiment analysis solutions or even sequence-based natural language solutions
We are going to use movie reviews to build this sentiment analysis application. The goal of this application is to produce positive and negative reviews based on the input raw text. For example, if the raw text is something like, This movie is good, then we need the model to produce a positive sentiment for it.
A sentiment analysis application will take us through a lot of processing steps that are needed to work with natural human languages...
