• Online, Self-Paced
Course Description

Machine learning regression models are used to predict numeric labels for the features of an item. In this course, you'll learn more about using regression models in the Azure Machine Learning Studio.

First, you'll learn about why regression models are used, the available types of regression models in machine learning, and the steps required to train a regression model. Next, you'll examine the best metrics for determining which regression model to use. You'll learn how to use a subset of data to train the regression model and run the training pipeline. Finally, you'll explore how to use an existing pipeline to create a new inference pipeline and create and deploy a predictive service.

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

Specialty Areas have been removed from the NICE Framework. With the recent release of the new NICE Framework data, updates to courses are underway. Until this course can be updated, this historical information is provided to give better context as to how it can help you with your cybersecurity goals.

Feedback

If you would like to provide feedback for this course, please e-mail the NICCS SO at NICCS@hq.dhs.gov.