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Democratizing Artificial Intelligence with UiPath

You're reading from   Democratizing Artificial Intelligence with UiPath Expand automation in your organization to achieve operational efficiency and high performance

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Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781801817653
Length 376 pages
Edition 1st Edition
Tools
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Authors (2):
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Fanny Ip Fanny Ip
Author Profile Icon Fanny Ip
Fanny Ip
Jeremiah Crowley Jeremiah Crowley
Author Profile Icon Jeremiah Crowley
Jeremiah Crowley
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Toc

Table of Contents (16) Chapters Close

Preface 1. Section 1: The Basics
2. Chapter 1: Understanding Essential Artificial Intelligence Basics for RPA Developers FREE CHAPTER 3. Chapter 2: Bridging the Gap between RPA and Cognitive Automation 4. Chapter 3: Understanding the UiPath Platform in the Cognitive Automation Life Cycle 5. Section 2: The Development Life Cycle with AI Center and Document Understanding
6. Chapter 4: Identifying Cognitive Opportunities 7. Chapter 5: Designing Automation with End User Considerations 8. Chapter 6: Understanding Your Tools 9. Chapter 7: Testing and Refining Development Efforts 10. Section 3: Building with UiPath Document Understanding, AI Center, and Druid
11. Chapter 8: Use Case 1 – Receipt Processing with Document Understanding 12. Chapter 9: Use Case 2 – Email Classification with AI Center 13. Chapter 10: Use Case 3 – Chatbots with Druid 14. Chapter 11: AI Center Advanced Topics 15. Other Books You May Enjoy

Approaching cognitive automation testing

As we continue through the automation life cycle once we have developed our automation, we can continue to test what was developed. While adding a cognitive component (Document Understanding, machine learning (ML) skills, and so on) brings additional complexities to automation from traditional rules-based robotic process automation (RPA), testing cognitive automation isn't too different from the traditional approach to testing automation.

In Chapter 6, Understanding Your Tools, we saw that when developing cognitive automation, we were essentially developing two distinct components: RPA and cognitive automation—we would build the ML skill first, then build RPA to leverage that ML skill. With this mindset, we can think of RPA and cognitive automation as modular components of the broader automation project, mimicking the design principle called separation of concerns (SoC).

SoC

This is a software design pattern where we separate...

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