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Automated Machine Learning with Microsoft Azure

You're reading from Automated Machine Learning with Microsoft Azure

Product type Book

Published in Apr 2021

Publisher Packt

ISBN-13 9781800565319

Pages 340 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Author (1):

Dennis Michael Sawyers

Table of Contents (17) Chapters

Preface

1. Section 1: AutoML Explained – Why, What, and How

2. Chapter 1: Introducing AutoML

3. Chapter 2: Getting Started with Azure Machine Learning Service

4. Chapter 3: Training Your First AutoML Model

5. Section 2: AutoML for Regression, Classification, and Forecasting – A Step-by-Step Guide

6. Chapter 4: Building an AutoML Regression Solution

7. Chapter 5: Building an AutoML Classification Solution

8. Chapter 6: Building an AutoML Forecasting Solution

9. Chapter 7: Using the Many Models Solution Accelerator

10. Section 3: AutoML in Production – Automating Real-Time and Batch Scoring Solutions

11. Chapter 8: Choosing Real-Time versus Batch Scoring

12. Chapter 9: Implementing a Batch Scoring Solution

13. Chapter 10: Creating End-to-End AutoML Solutions

14. Chapter 11: Implementing a Real-Time Scoring Solution

15. Chapter 12: Realizing Business Value with AutoML

16. Other Books You May Enjoy

Technical requirements

In this chapter, you will be creating an Azure Kubernetes Service (AKS) instance through AML studio and creating real-time scoring endpoints using the Diabetes-AllData-Regression-AutoML that you created in Chapter 4, Building an AutoML Regression Solution.

As such, you will need a working internet connection, an Azure Machine Learning Service (AMLS) workspace, and a compute instance. You will also need permission to create an AKS cluster. If you are using a personal account, this will not be an issue.

The following are the prerequisites for the chapter:

Have access to the internet
Have a web browser, preferably Google Chrome or Microsoft Edge Chromium
Have a Microsoft Azure account
Have created an AMLS workspace
Have created the compute-cluster compute cluster in Chapter 2, Getting Started with Azure Machine Learning Service
Understand how to navigate to the Jupyter environment from an Azure compute instance as demonstrated...

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Authors (1)

Dennis Michael Sawyers

Dennis Michael Sawyers is a senior cloud solutions architect (CSA) at Microsoft, specializing in data and AI. In his role as a CSA, he helps Fortune 500 companies leverage Microsoft Azure cloud technology to build top-class machine learning and AI solutions. Prior to his role at Microsoft, he was a data scientist at Ford Motor Company in Global Data Insight and Analytics (GDIA) and a researcher in anomaly detection at the highly regarded Carnegie Mellon Auton Lab. He received a master's degree in data analytics from Carnegie Mellon's Heinz College and a bachelor's degree from the University of Michigan. More than anything, Dennis is passionate about democratizing AI solutions through automated machine learning technology.

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