Set up an Azure Machine Learning Service
John Ellis
0 h 45 m
Lecture Overview
Get introduced to Azure Machine Learning Service. In this course you will learn about the core environment for working with Azure Machine Learning: the Workspace. We also introduce the two primary concepts within the workspace required to make things happen: Data stores and Compute Contexts.This course covers one of the objective areas that help you in preparing for the. DP-100: Designing and Implementing a Data Science Solution on Azure exam.

Related Learning Path(s):
DP-100: Designing and Implementing an Azure Data Science Solution on Azure
  • Describe what Azure Machine Learning Service is
  • Describe and understand what a Workspace is
  • Be able to manage data stores within the Workspace
  • Understand Compute Contexts and where to find them in the Workspace
Lecture Modules
This module is divided into three sections. First, we’ll look high-level at what Azure Machine Learning Service is. Next, we will explore the ways in which we can create an Azure Machine Learning Workspace and what settings we must choose when doing so. Finally we will then examine how to view and manage the contents of our workspace by using the new Azure Machine Learning studio graphical interface within the Azure Portal environment.
This module is divided into 2 sections: How to register and manage data stores and how to create and manage data sets from those data stores . We will first review what datastores and datasets are, then we will discuss and demo the creation of each within our Azure Machine Learning workspace.
This module is divided into 3 sections. First we will learn about Compute Instances and create one. Next we learn about the different types of compute offered by Azure Machine Learning and when we will choose each. Finally we will demonstrate how to create compute targets using both the Azure Machine Learning studio as well as the Azure Machine Learning SDK for Python. 
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