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AI Product Manager's Handbook

You're reading from   AI Product Manager's Handbook Build, integrate, scale, and optimize products to grow as an AI product manager

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781835882849
Length 484 pages
Edition 2nd 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 (26) Chapters Close

Preface 1. Part 1: Lay of the Land – Terms, Infrastructure, Types of AI, and Products Done Well
2. Understanding the Infrastructure and Tools for Building AI Products FREE CHAPTER 3. Model Development and Maintenance for AI Products 4. Deep Learning Deep Dive 5. Commercializing AI Products 6. AI Transformation and Its Impact on Product Management 7. Part 2: Building an AI-Native Product
8. Understanding the AI-Native Product 9. Productizing the ML Service 10. Customization for Verticals, Customers, and Peer Groups 11. Product Design for the AI-Native Product 12. Benchmarking Performance, Growth Hacking, and Cost 13. Managing the AI-Native Product 14. Part 3: Integrating AI into Existing Traditional Software Products
15. The Rising Tide of AI 16. Trends and Insights Across Industry 17. Evolving Products into AI Products 18. The Role of AI Product Design 19. Managing the Evolving AI Product 20. Part 4: Managing the AI PM Career
21. Starting a Career as an AI PM 22. What Does It Mean to Be a Good AI PM? 23. Maturing and Growing as an AI PM 24. Other Books You May Enjoy
25. Index

Summary

In this chapter, we covered the NPD cycle and a review of the common AI/ML model types. We also covered an overview of how to train, deploy, and troubleshoot the models that are chosen, giving us a reasonable foundation on what to expect when working with models in production. We also touched on some of the most important ethical practices, coming from some of the most rigorous standards that exist, when building products with AI/ML components.

If you’re interested in expanding further on building ethical AI, we’ve provided some handy links in the following section for additional study. Keep in mind that we’re at a critical juncture with regard to AI/ML ethics. We’re building this ship as we’re sailing it, and as AI/ML products continue to enter the zeitgeist, we will see additional measures put in place to reign in the potential harm caused by improper AI deployments through the diligent work of lawmakers and activists. We’re not there...

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