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AI Product Manager's Handbook

You're reading from   AI Product Manager's Handbook The ultimate playbook to unlock AI product success with real-world insights and strategies

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Product type Paperback
Published in Nov 2024
Publisher Packt
ISBN-13 9781835882849
Length 488 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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Toc

Table of Contents (27) Chapters Close

Preface 1. Part 1: Lay of the Land – Terms, Infrastructure, Types of AI, and Products Done Well FREE CHAPTER
2. Understanding the Infrastructure and Tools for Building AI Products 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. Unlock Your Book’s Exclusive Benefits 25. Other Books You May Enjoy
26. Index

ML versus DL – understanding the difference

In this section, we will explore the relationship between ML and DL and the way in which they bring their own sets of expectations, explanations, and elucidations to builders and users alike. Whether you work with products that incorporate ML models that have been around since the 50s or use cutting-edge models that have sprung into use recently, you’ll want to understand the implications either way. Incorporating ML or DL into your product will have different repercussions. Most of the time, when you see an AI label on a product, it’s built using ML or DL, so we want to make sure you come out of this chapter with a firm understanding of how these areas differ and what this difference will tangibly mean for your future products.

As a PM, you’re going to need to build a lot of trust with your technical counterparts so that, together, you can build an amazing product that works as well as it can technically...

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