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

Product type Paperback

Published in Apr 2021

Publisher Packt

ISBN-13 9781800565319

Length 340 pages

Edition 1st Edition

Languages

Python

Tools

Azure

Concepts

Machine Learning

Authors (2):

Dennis Michael Sawyers

Dennis Sawyers

View More author details

Table of Contents (17) Chapters

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

Architecting AutoML solutions

Architecting AutoML solutions refers to drawing end-to-end diagrams. These act as blueprints for how you should build out your solution, and also can be used to explain to your end users how everything works. While many IT solutions are complex and can take many forms, AutoML-based solutions follow standard patterns that require you to make a few important decisions.

In this section, you'll first learn what decisions to make before architecting a decision. Then, you will learn how to architect an end-to-end batch scoring solution and an end-to-end real-time scoring solution that's easy to explain to end users. Although the architecture may be simplified, the more standard it is, the easier it is to implement, explain, and understand.

Making key architectural decisions for AutoML solutions

When drawing an architectural diagram, there are several key considerations you need to make, the most important being whether you need to make a batch...