Project architecture

The simple project will be split into two primary functions:

• Training and evaluation
• Model runs

This split between functionality models real-world production applications that utilize machine learning, as there are often teams dedicated to each.

For those who wish to start with a completed project and follow along with the rest of this section, you can get the code from here: https://github.com/PacktPublishing/Hands-On-Machine-Learning-With-ML.NET/tree/master/chapter02

The following screenshot shows the project breakdown in Solution Explorer of Visual Studio. As mentioned earlier, the project is split into two main classes—Predictor and Trainer:

The Trainer class contains all the model building and evaluation code, while the Predictor class, as the name implies, contains the code to run predictions with a trained model.

The BaseML class is what we will be using in subsequent chapters and expanding upon throughout the remainder of the book. The idea behind this class is to cut down on the DRY (don't repeat yourself) violations and to create a cohesive and easy to iterate framework. The Constants class further assists this idea—to cut down on magic strings as we move into more complex applications; this design will be used in all future chapter projects.

Lastly, the Program class is the main entry point for our console application.