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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
Author Profile Icon Andreas Botsikas
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

To get the most out of this book

This book tries to provide you with everything you need to learn. The Further reading section of each chapter contains links to pages that will help you deep dive, into topics that are peripheral to the contents of this book. It will help if you have some basic familiarity with the Azure portal and have read some Python code in the past.

In this book, we guide you to use the Notebooks experience available within the AzureML studio. If you want to execute the same code on your workstation instead of the cloud-based experience, you will need a Python environment to run Jupyter notebooks. The easiest way to run Jupyter notebooks on your workstation is through VSCode, a free cross-platform editor with fantastic Python support. You will also need to install Git in your workstation to clone the book’s GitHub repository.

If you are using the digital version of this book, we advise you to type the code yourself or access the code from the book's GitHub repository (a link is available in the next section). Doing so will help you avoid any potential errors related to the copying and pasting of code.

If you face any issue executing the code, ensure that you have cloned the latest version from the GitHub repository. If the problem persists, feel free to open a GitHub issue to describe the issue you are facing and help you solve it.

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