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Azure Data Scientist Associate Certification Guide

You're reading from   Azure Data Scientist Associate Certification Guide A hands-on guide to machine learning in Azure and passing the Microsoft Certified DP-100 exam

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Product type Paperback
Published in Dec 2021
Publisher Packt
ISBN-13 9781800565005
Length 448 pages
Edition 1st Edition
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Authors (2):
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Andreas Botsikas Andreas Botsikas
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Andreas Botsikas
Michael Hlobil Michael Hlobil
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Michael Hlobil
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Table of Contents (17) Chapters Close

Preface 1. Section 1: Starting your cloud-based data science journey
2. Chapter 1: An Overview of Modern Data Science FREE CHAPTER 3. Chapter 2: Deploying Azure Machine Learning Workspace Resources 4. Chapter 3: Azure Machine Learning Studio Components 5. Chapter 4: Configuring the Workspace 6. Section 2: No code data science experimentation
7. Chapter 5: Letting the Machines Do the Model Training 8. Chapter 6: Visual Model Training and Publishing 9. Section 3: Advanced data science tooling and capabilities
10. Chapter 7: The AzureML Python SDK 11. Chapter 8: Experimenting with Python Code 12. Chapter 9: Optimizing the ML Model 13. Chapter 10: Understanding Model Results 14. Chapter 11: Working with Pipelines 15. Chapter 12: Operationalizing Models with Code 16. Other Books You May Enjoy

Technical requirements

You will require access to an Azure subscription. Within that subscription, you will need a resource group named packt-azureml-rg. You will need to have either a Contributor or Owner Access control (IAM) role on the resource group level. Within that resource group, you should have already deployed a machine learning resource, named packt-learning-mlw. These resources should be already available to you if you followed the instructions in Chapter 2, Deploying Azure Machine Learning Workspace Resources.

Additionally, you will require a basic understanding of the Python language. The code snippets in this chapter target Python version 3.6 or later. You should also be familiar with working with notebooks within AzureML studio; this is something that was covered in Chapter 7, The AzureML Python SDK.

This chapter assumes you have registered the loans dataset that you generated in Chapter 10, Understanding Model Results. It also assumes that you have created a...

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