Predict Income Levels Using Azure Machine Learning Studio
This lab has been outdated due to Microsoft deprecating creating new Machine Learning Studio (classic) resources. A new lab, Predict Income Levels Using Azure Machine Learning Designer, has been created using the new generation of Machine Learning Studio.
Beginning 1st December 2021, Microsoft has deprecated creating new Machine Learning Studio (classic) resources. Please refer to the Migrate to Azure Machine Learning documentation for more information.
Lab Overview
Microsoft Azure Machine Learning Studio is a drag-and-drop tool that allows you to visually and collaboratively build, test, and deploy machine learning models. In this Lab, you will predict income levels using census data and compare the performance of two trained models in Azure Machine Learning Studio. You will see how easy it is to build powerful models without having to write a single line of code!
Lab Objectives
Upon completion of this Lab you will be able to:
- Build and evaluate machine learning models with Azure Machine Learning Studio Experiments
- Compare models from within Azure Machine Learning Studio
- Explore datasets visually using Azure Machine Learning Studio
Lab Prerequisites
You should be familiar with:
- Navigating the Azure Portal
Lab Environment
Before completing the Lab instructions, the environment will look as follows:
After completing the Lab instructions, the environment should look similar to:
Logan has been involved in software development and research since 2007 and has been in the cloud since 2012. He is an AWS Certified DevOps Engineer - Professional, AWS Certified Solutions Architect - Professional, Microsoft Certified Azure Solutions Architect Expert, MCSE: Cloud Platform and Infrastructure, Google Cloud Certified Associate Cloud Engineer, Certified Kubernetes Security Specialist (CKS), Certified Kubernetes Administrator (CKA), Certified Kubernetes Application Developer (CKAD), and Certified OpenStack Administrator (COA). He earned his Ph.D. studying design automation and enjoys all things tech.