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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
Author (1):
Dennis Michael Sawyers Dennis Michael Sawyers
Profile icon 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

Using AutoML in other Microsoft products

In this book, you've learned how to use AutoML on Azure, but you can also use AutoML in a wider suite of Microsoft products. While you can easily create and productionalize just about any AutoML solution following the architectural patterns in the Architecting AutoML solutions section of this chapter, there are certain scenarios in which you may want to use AutoML on other Microsoft platforms. You can find AutoML in the following places:

  • PowerBI
  • Azure Synapse Analytics
  • ML.NET
  • HDInsight
  • SQL Server
  • Azure Databricks

Even though AutoML is available for these services, there are many differences of which you should be aware. Some services are code-free while others are code-only. Some services preclude you from training forecasting algorithms and others are based on entirely different ML frameworks. In this section, you will be guided through the general capabilities service by service.

Using AutoML within...

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