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Automated Machine Learning with Microsoft Azure

You're reading from   Automated Machine Learning with Microsoft Azure Build highly accurate and scalable end-to-end AI solutions with Azure AutoML

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Product type Paperback
Published in Apr 2021
Publisher Packt
ISBN-13 9781800565319
Length 340 pages
Edition 1st Edition
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Authors (2):
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Dennis Michael Sawyers Dennis Michael Sawyers
Author Profile Icon Dennis Michael Sawyers
Dennis Michael Sawyers
Dennis Sawyers Dennis Sawyers
Author Profile Icon Dennis Sawyers
Dennis Sawyers
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Toc

Table of Contents (17) Chapters Close

Preface 1. Section 1: AutoML Explained – Why, What, and How
2. Chapter 1: Introducing AutoML FREE CHAPTER 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

Determining batch versus real-time scoring scenarios

When confronted with real business use cases, it is often difficult to distinguish how you should deploy your ML model. Many data scientists make the mistake of implementing a batch solution when a real-time solution is required, while others implement real-time solutions even when a cheaper batch solution would be sufficient.

In the following sections, you will look at different problem scenarios and solutions. Read each of the six scenarios and determine whether you should implement a real-time or batch inferencing solution. First, you will look at every scenario. Then, you will read each answer along with an explanation.

Scenarios for real-time or batch scoring

In this section, you are presented with six scenarios. Read each carefully and decide whether a batch or real-time scoring solution is most appropriate.

Scenario 1 – Demand forecasting

A fast-food company is trying to determine how many bags of frozen...

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