Summary

You have added to your repertoire by successfully training a classification model using the AML Python SDK. You have loaded in data, heavily transformed it using pandas and Numpy, and built a toy AutoML model. You then registered that model to your AMLS workspace.

You can now start building classification models with your own data. You can easily solve both binary and multiclass classification problems, and you can present results to the business in a way they understand with confusion matrices. Many of the most common business problems, such as customer churn, are classification problems, and with the knowledge you learned in this chapter, you can solve those problems and earn trust and respect in your organization.

The next chapter, Chapter 6, Building an AutoML Forecasting Solution, will be vastly different from the previous two chapters. Forecasting problems have many more settings to use and understand compared to classification and regression problems, and they...