In this chapter, we are going to build an iOS application to do sentiment analysis over text and image through user input. We will use existing data models that were built for the same purpose by using LinearSVC, and convert those models into core machine learning (ML) models for ease of use in our application. 

Sentiment analysis is the process of identifying a feeling or opinion that is inspired by any given data in the form of text, image, audio, or video. There are a lot of use cases for sentiment analysis. Even now, political parties can easily identify the general mindset of the people who are going to elect them and they also have the potential to change that mindset. 

Let's take a look at building our own ML model on sentiment analysis from an existing dataset. In this chapter, we will look at the following topics: 

• Building the ML model using scikit-learn
• Linear Support Vector Classification (LinearSVC)
• Building an iOS application