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The AI Product Manager's Handbook

You're reading from   The AI Product Manager's Handbook Develop a product that takes advantage of machine learning to solve AI problems

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Product type Paperback
Published in Feb 2023
Publisher Packt
ISBN-13 9781804612934
Length 250 pages
Edition 1st Edition
Languages
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Author (1):
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Irene Bratsis Irene Bratsis
Author Profile Icon Irene Bratsis
Irene Bratsis
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Table of Contents (19) Chapters Close

Preface 1. Part 1 – Lay of the Land – Terms, Infrastructure, Types of AI, and Products Done Well
2. Chapter 1: Understanding the Infrastructure and Tools for Building AI Products FREE CHAPTER 3. Chapter 2: Model Development and Maintenance for AI Products 4. Chapter 3: Machine Learning and Deep Learning Deep Dive 5. Chapter 4: Commercializing AI Products 6. Chapter 5: AI Transformation and Its Impact on Product Management 7. Part 2 – Building an AI-Native Product
8. Chapter 6: Understanding the AI-Native Product 9. Chapter 7: Productizing the ML Service 10. Chapter 8: Customization for Verticals, Customers, and Peer Groups 11. Chapter 9: Macro and Micro AI for Your Product 12. Chapter 10: Benchmarking Performance, Growth Hacking, and Cost 13. Part 3 – Integrating AI into Existing Non-AI Products
14. Chapter 11: The Rising Tide of AI 15. Chapter 12: Trends and Insights across Industry 16. Chapter 13: Evolving Products into AI Products 17. Index 18. Other Books You May Enjoy

Expert systems

An expert system is a generic term meant to describe some sort of rule-based engine that’s been continuously refined and optimized over time. They were used heavily in the past in medical and legal use cases before ML became popularized. Although there are some companies that may still rely on them, their relevance has receded. They have a user interface (UI) and are powered by an inference engine that is connected to a knowledge base of some sort. It’s a more basic form of AI that’s made up of If Then statements. A rule-based engine means there are a set of pre-programmed instructions and algorithms that have been programmed into the backbone of how a product or system functions and there is an absence of self-learning. This means that ML models are not used and the system is not learning over time. Though this might sound like a dumb system, it’s still considered AI because it still might be functioning in a way that mimics how a human might...

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