Azure Data Scientist Associate: Machine Learning Clustering Models
Azure 2021 | Intermediate
- 9 videos | 57m 9s
- Includes Assessment
- Earns a Badge
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.
WHAT YOU WILL LEARN
discover the key concepts covered in this coursedescribe the available types of clustering models in machine learningdescribe the steps required to train a clustering modeluse the Azure Machine Learning designer to train a clustering modelcreate a K-means clustering model in Azure Machine Learning Studio
evaluate a clustering model by using an evaluate model in Azure Machine Learning Studiouse an existing pipeline to create a new inference pipeline to create a predictive service for a clustering modeldeploy an clustering model based inference pipeline that can be used by clientssummarize the key concepts covered in this course
IN THIS COURSE
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