Tuning Hyperparameters with Hyperdrive in Azure Machine Learning

Lab Steps

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Logging into the Microsoft Azure Portal
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Launching Azure Machine Learning Studio
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Creating an Azure Notebook
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Working Through the Azure Notebook

The hands-on lab is part of this learning path

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DifficultyIntermediate
Time Limit1h
Students122
Ratings
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Description

In the world of data science, model parameters are the elements generated from training a dataset. In contrast, a hyperparameter is a parameter used to control the outcome of training the model. Machine learning models are deep and complex and require several hyperparameters to build the best model. There is no logical formula for obtaining the best hyperparameter values. These values must be tweaked and analyzed. Like tuning a musical instrument, data scientists must tune their training models to achieve the best possible outcome. 

Hyperparameter optimization can become a tedious task of tweaking values and re-running experiments. Hyperdrive is a Python package that automates this process in Azure Machine Learning. Deploying experiments with Hyperdrive dramatically reduces the process of manually tweaking the hyperparameters used for each experiment.

In this lab, you will dive into Azure Notebooks and launch a Jupyter notebook to create a Hyperdrive experiment and perform hyperparameter tuning against a regression training model.

Learning Objectives

Upon completion of this lab you will be able to:

  • Use Hyperdrive to tune hyperparameters
  • Find a model that has optimal hyperparameter values
  • Create and run Azure Notebooks
  • Manage a workspace using the Azure Machine Learning SDK

Intended Audience

This lab is intended for:

  • Individuals studying to take the Azure DP-100 exam
  • Anyone interested in learning how to use the Azure Machine Learning SDK

Lab Prerequisites

You should be familiar with:

  • Basic concepts of Azure Machine Learning
  • Experience with Python is not required but preferred. 
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About the Author
Students306
Labs6
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Luke currently serves as a Cloud Labs Developer at Cloud Academy. His background is infrastructure development using Terraform. He is an Azure DevOps Engineer Expert, Azure Administrator Associate, and HashiCorp Certified - Terraform Associate.