Introduction

Completed

Data is a fundamental element in any machine learning workload. You need data to train a model and you create data when using a model to generate predictions.

To work with data in Azure Machine Learning, you can access data by using Uniform Resource Identifiers (URIs). When you work with a data source or a specific file or folder repeatedly, you can create datastores and data assets within the Azure Machine Learning workspace. Datastores and data assets allow you to securely store the connection information to your data.

In this module, you learn how to create and use URIs, datastores, and data assets in Azure Machine Learning.