Summary

In this chapter, you have explored Azure Machine Learning datastores, which enable you to connect to datastore services. You have also learned about Azure Machine Learning datasets, empowering you to create a reference to a location within a datastore. These assets within Azure Machine Learning can be created through the UI for a low code experience, as well as through the Azure Machine Learning Python SDK or the Azure Machine Learning CLI. Once these references are created, datasets can be retrieved and used through the Azure Machine Learning Python SDK. Once the dataset has been retrieved, it can easily be converted into a pandas dataframe for use within your code. You have also seen how to use datasets within an Azure Machine Learning job by passing them as input to the job.

In Chapter 3, Training Machine Learning Models in AMLS, you will explore training models; experiments will become a key asset in your toolbelt, enabling traceability as you build your model in AMLS...