Now that we have completed our deep dive, there are a couple of additional elements that could possibly further enhance the application. A few ideas are discussed here.
Self-training based on the end user's input
One of the advantages, as noted in the opening section of this chapter, is the ability to utilize transfer learning in dynamic applications. Unlike previous example applications that have been reviewed in this book, this application could actually allow the end user to select a series (or folder) of images, and with a few code changes, build the new .tsv file and train a new model. For a web application or commercial product, this would provide a high value and would also reduce the burden on you to, for instance, obtain images of every type—a daunting, and more than likely futile, goal.
Logging
As mentioned in the Logging section of Chapter 10, Using ML.NET with UWP, having a desktop application has its pros and cons. The biggest...
