• Online, Self-Paced
Course Description

Machine learning clustering models are used to group similar items based on their features and use unsupervised learning. In this course, you'll learn about using clustering models in the Azure Machine Learning Studio.

First, you'll explore the available types of clustering models in Azure Machine Learning Studio and the steps required to train a clustering model. Next, you'll learn how to train and evaluate a clustering model. Next, you'll examine how to create a K-means clustering model in Azure Machine Learning Studio. Finally, you'll learn how to create and deploy a new inference pipeline to create a predictive service for a clustering model.

This course is one in a collection that prepares learners for the Designing and Implementing a Data Science Solution on Azure (DP-100) exam.

Learning Objectives

{"discover the key concepts covered in this course"}

Framework Connections

The materials within this course focus on the NICE Framework Task, Knowledge, and Skill statements identified within the indicated NICE Framework component(s):

Specialty Areas

  • Network Services