To train and deploy models using Microsoft Azure Machine Learning designer, you need compute power on which to run the training process, and to test the trained model after deploying it.

Create compute targets

Compute targets are cloud-based resources on which you can run model training and data exploration processes.

1. In  Microsoft https://ml.azure.com/ , view the Compute page (under Manage ). This is where you manage the compute targets for your data science activities. There are four kinds of compute resources you can create:

2. On the Compute Instances tab, add a new compute instance with the following settings. You'll use this as a workstation from which to test your model:

3. While the compute instance is being created, switch to the Compute Clusters tab, and add a new compute cluster with the following settings. You'll use this to train a machine learning model:

Note

If you decide not to complete this module, be sure to stop your compute instance to avoid incurring unnecessary charges to your Microsoft Azure subscription.

The compute targets will take some time to be created. You can move onto the next unit while you wait.