- Lab
- AI
- Cloud
Creating a Regression Model with Azure ML Designer
In this hands-on lab, you are working as a data scientist for Bike4Ever, a bike rental company. You’ve been asked to come up with a model that can be used to predict bike rentals based on factors such as weather, temperature, day of the week, and more. You’ll use Azure Machine Learning studio and Azure Machine Learning designer to create a regression model that will predict bike rentals.
Path Info
Table of Contents
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Challenge
Open the Azure ML Studio and Create a New Dataset
In the Azure ML studio, download the dataset as a CSV file from Microsoft and use it to create a new dataset.
Note: If at any time the Azure page is not displaying all the page elements, try adjusting your browser settings to Zoom out/in.
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Challenge
Review the Dataset
Take a look at the data you’re working with and see if there are any missing values or values that will cause issues.
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Challenge
Design a Pipeline to Predict Bike Rentals
Using the Azure Machine Learning designer, drag and drop modules to create a pipeline that will train a regression model to predict bike rentals. When setting the compute type, set it to Compute cluster.
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Challenge
Review the Results
Take a look at some of the metrics for the run. For example, the R2 score or the root mean squared error.
What's a lab?
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.
Provided environment for hands-on practice
We will provide the credentials and environment necessary for you to practice right within your browser.
Guided walkthrough
Follow along with the author’s guided walkthrough and build something new in your provided environment!
Did you know?
On average, you retain 75% more of your learning if you get time for practice.