As mentioned earlier, the application we will be creating is a file type classifier. Given a set of attributes statically extracted from a file, the prediction will return if it is a document, an executable, or a script. For those of you who have used the Linux file command, this is a simplified version but based on machine learning. The attributes included in this example aren't the definitive list of attributes, nor should they be used as-is in a production environment; however, you could use this as a starting point for creating a true ML-based replacement for the Linux file command.
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/chapter05.
Exploring the project architecture
Building on the project architecture and code we created in previous chapters, the major change architecturally is in the...
