Using Azure Automated ML

1.5 hours
  • 5 Learning Objectives

About this Hands-on Lab

In this hands-on lab, you are working as a data scientist for Sam’s Taxi, a taxi cab company. You’ve been asked to come up with a model that can be used to predict fare prices based on length of drive and time it takes to drive there. You’ll use Azure Machine Learning studio and Azure automated machine learning to create a regression model that will predict fare prices. You’ll also get a chance to deploy your model to an Azure Container Instance and test how accurate it is.

Learning Objectives

Successfully complete this lab by achieving the following learning objectives:

Open the Azure ML Studio and Create a New Dataset

In the Azure ML studio, create a new dataset using the taxi fare data file from Microsoft.

Configure and Start the Automated ML Run

Change the timeout of the run to 30 minutes:

  1. Click on View additional configuration settings.
  2. Open Exit criterion.
  3. Set the training job time (hours) to .5 so it will stop after approximately 30 minutes.
Review Results

Take a look at some of the metrics for the run, like the R2 score or the root mean squared error.

Deploy the Model to an Azure Container Instance

Deploy the model to a web service. Before deploying, click Advanced and change both the CPU reserve capacity and memory reserve capacity to 1. Otherwise, the resources will be deleted.

Test Your Newly Deployed Model

Use some values from the CSV file and see how accurate the predicted value is compared to the actual value.

Additional Resources

In this lab scenario, you are working as a data scientist for Sam's Taxi, a taxi cab company. You’ve been asked to come up with a model that can be used to predict fare prices based on length of drive and time it takes to drive there.

Use Azure Machine Learning studio and Azure automated machine learning to create a regression model that will predict fare prices. Then, deploy your model to an Azure Container Instance and test how accurate it is.


Log in to the Azure portal using the credentials provided. Make sure you're using an incognito window to ensure you aren't logged in to your own account.

What are Hands-on Labs

Hands-on Labs are real environments created by industry experts to help you learn. These environments help you gain knowledge and experience, practice without compromising your system, test without risk, destroy without fear, and let you learn from your mistakes. Hands-on Labs: practice your skills before delivering in the real world.

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