Explore best practices for DP-100: Designing and implementing a data science solution on Azure learning path 8

Completed

DP-100: Learning Path 8 Optimize model training in Azure Machine Learning

Learning Path 8 Overview

As you begin to teach this learning path, get familiar with what the students learn during the learning path. In this learning path student learn about optimizing the learning path training in Azure Machine Learning and running the pipelines in Azure Machine Learning. Students will also learn about hyper parameter tuning and how to use the Azure Machine Learning SDK to apply hyper parameter tuning to find the best learning path.

This learning path consists of four focus areas:

• Understand pipeline components and create them
• Build, configure, and run AML Pipeline
• Understand hyper parameters
• Configure various hyper parameter tuning options on AML

Learning Path 8 Tips and Tricks

• Emphasize the importance of workflow in Machine Learning
• Differentiate between parameters and hyperparameters

Learning Path 8 Demos (optional)

• Visit an existing pipeline or YAML file
• Use hyperparameter tuning document to show the different configuration options

Learning Path 8 Labs (optional)

• Lab 8.1: Perform hyperparameter tuning with a sweep job
• Lab 8.2: Run pipelines in Azure Machine Learning