Summary

Introduction to Azure Machine Learning

Data Science Course

4.6

Summary

In this module, you learned how to:

Provision an Azure Machine Learning workspace.
Use tools and interfaces to work with Azure Machine Learning.
Run code-based experiments in an Azure Machine Learning workspace.

Check your knowledge

1. Which of the following descriptions accurately describes Azure Machine Learning?

A Python library that you can use as an alternative to common machine learning frameworks like Scikit-Learn, PyTorch, and Tensorflow.

A cloud-based platform for operating machine learning solutions at scale.

An application for Microsoft Windows that enables you to create machine learning models by using a drag and drop interface.

2. Which edition of Azure Machine Learning workspace should you provision if you only plan to use the graphical Designer tool to train machine learning models?

Basic

Enterprise

3. You are using the Azure Machine Learning Python SDK to write code for an experiment. You must log metrics from each run of the experiment, and be able to retrieve them easily from each run. What should you do?

Add print statements to the experiment code to print the metrics.

Save the experiment data in the outputs folder.

Use the log* methods of the Run class to record named metrics.