Search icon CANCEL
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Conferences
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Arrow left icon
Product type Paperback
Published in Apr 2022
Publisher Packt
ISBN-13 9781801817653
Length 376 pages
Edition 1st Edition
Tools
Arrow right icon
Authors (2):
Arrow left icon
Fanny Ip Fanny Ip
Author Profile Icon Fanny Ip
Fanny Ip
Jeremiah Crowley Jeremiah Crowley
Author Profile Icon Jeremiah Crowley
Jeremiah Crowley
Arrow right icon
View More author details
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

QnA

  1. What are the characteristics of the Document Understanding framework?
    • Taxonomy, digitization, classification, extraction, and export.
  2. Can you digitize a document without an OCR engine?
    • Yes, you can; however, the digitization activity of the Document Understanding framework will require an OCR engine, even if OCR is unneeded.
  3. When should the Classification Station or Validation Station be used?
    • They should be used when automation confidence is not high and human validation is needed to augment automation. They should also be used when closing the feedback loop and retraining via human validation.
  4. Is AI Center limited to out-of-the-box ML packages?
    • No. AI Center can handle custom ML models made with Python in addition to the out-of-the-box packages it offers.
  5. When is CV best used?
    • CV is best for applications that contain unreliable selectors or VDI/VM environments where selectors cannot be captured.
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at €18.99/month. Cancel anytime