You're reading from AI and Business Rule Engines for Excel Power Users Capture and scale your business knowledge into the cloud – with Microsoft 365, Decision Models, and AI tools from IBM and Red Hat

Product type Paperback

Published in Mar 2023

Publisher Packt

ISBN-13 9781804619544

Length 386 pages

Edition 1st Edition

Languages

Power Query

Tools

Excel

Concepts

Information Management

Authors (2):

Paul Browne (GBP)

ALEX PORCELLI

View More author details

Table of Contents (22) Chapters

Preface

1. Part 1:The Problem with Excel, and Why Rule-Based AI Can Be the Solution FREE CHAPTER

2. Chapter 1: Wrestling with Excel? You Are Not Alone

3. Chapter 2: Choosing an AI and Business Rules Engine – Why Drools and KIE?

4. Chapter 3: Your First Business Rule with the Online KIE Sandbox

5. Part 2: Writing Business Rules and Decision Models – with Real-Life Examples

6. Chapter 4: More Decision Models, Business Rules, and Decision Tables

7. Chapter 5: Sharing and Deploying Decision Models Using OpenShift and GitHub

8. Chapter 6: Calling Business Rules from Excel Using Power Query

9. Part 3: Extending Excel, Decision Models, and Business Process Automation into a Complete Enterprise Solution

10. Chapter 7: Using Business Rules in Excel with Visual Basic, Script Lab, or Office Scripts

11. Chapter 8: Using AI and Decision Services Within Power Automate Workflows

12. Chapter 9: Advanced Expressions, Decision Models, and Testing

13. Part 4: Next Steps in AI, Machine Learning, and Rule Engines

14. Chapter 10: Scaling Rules in Business Central with Docker and the Cloud

15. Chapter 11: Rules-Based AI and Machine Learning AI – Combining the Best of Both

16. Chapter 12: What Next? A Look inside Neural Networks, Enterprise Projects, Advanced Rules, and the Rule Engine

17. Index

Why subscribe?

18. Other Books You May Enjoy

Appendix A - Introduction to Visual Basic for Applications

Introduction to macros and VBA

1. Appendix B - Testing Using VSCode, Azure, and GitHub Codespaces

2. Appendix C - Troubleshooting Docker

This chapter was written to give you the confidence and the desire to know more about machine learning. We introduced several key topics that your interests may lead you toward, from learning more about Azure and Azure ML to taking a deeper dive into Python notebooks and the different algorithms implemented in them. All of these topics have Packt Publishing books available on them.

At this point, it is also worth (re)viewing the Kogito and Drools documentation with a focus on the AI tools and integration, since much of the information there will now make a lot more sense to you, as well as giving practical steps on how to deploy combined rules and ML decision services.

One non-Packt Publishing book that I highly recommend is Mathematics for Machine Learning. It’s available as a free/open book from https://mml-book.github.io/. While it is very clearly written and accessible, it is still a math book. So, while it is a fascinating read and will enhance your...