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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
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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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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

Chapter 9: Use Case 2 – Email Classification with AI Center

A classic use for machine learning (ML) is text classification. Every organization, irrespective of the industry, has a use case for classifying text. Examples of text classification use cases include routing emails to corresponding folders or routing service requests to relevant teams. A lot of this work is still manual, requiring an individual to review the text and use their judgment to interpret and classify the text's contents. Fortunately, with UiPath's AI Center, we can create cognitive automation to apply intelligent understanding of text, potentially reducing the need for manual work.

By having a full understanding of AI Center, we will work together to build cognitive automation that can interpret and classify text. As we build a use case, we will follow a similar development life cycle as outlined in the previous chapters. We will start with understanding the current state of our automation...

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