Summary

This chapter introduced the pipeline designer, which allows us to create AzureML pipelines via drag and drop. You built your first training pipeline based on the churn dataset and the Two-Class Decision Forest model. We discussed three pipeline types, authored the training pipeline, created a batch pipeline, and developed and deployed a real-time pipeline.

This chapter concludes the no-code, low-code features that AzureML provides. In the next chapter, you will start working on the AzureML Python SDK. The AzureML Python SDK allows you to train models and create machine learning pipelines through code, which is critical for the DP-100 exam.