Summary
We have covered a lot of topics in this chapter. We have shown you how to train an ML model using the AML Designer, which requires no coding. It is a great fit for citizen data scientists or advanced data scientists who would like to explore different algorithms quickly and evaluate their performance without having to write a lot of code to do so. Next, you learned how to train an ML model through the AML Python SDK, running on both a compute instance and a compute cluster for more compute-intensive ML jobs.
In the next chapter, you will learn how to tune hyperparameters for your ML models using AML HyperDrive.
