As mentioned earlier, the application that we will be creating is an image classification application, specifically allowing the user to select an image and determine whether it is either food or water. This is achieved through the aforementioned and included, pre-trained TensorFlow Inception model. The first time that the application is run, the ML.NET version of the model is trained with the images and the tags.tsv file (to be reviewed in the next section).
As with previous chapters, the completed project code, sample dataset, and project files can be downloaded here: https://github.com/PacktPublishing/Hands-On-Machine-Learning-With-ML.NET/tree/master/chapter12.
Exploring the project architecture
In this chapter, we will dive into a WPF desktop application. As mentioned in the first section of this chapter, we will be using the WPF framework to create our application. You might be asking, why not a UWP application such as the browser...
