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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

The new – exploring DL

Part of our intention with separating ML and DL conceptually in this book is really to create associations in the reader’s mind. For most technical folks in the field, there are specific models and algorithms that come up when you see “ML” versus “DL” as a descriptor on a product. Quick reminder here that DL is a subset of ML. If you ever get confused by the two terms, just remember that DL is a form of ML that’s grown and evolved to form its own ecosystem. Our aim is to demystify that ecosystem as much as possible so that you can confidently understand the dynamics at play with DL products as a product manager.

The foundational idea of DL is centered around our own biological neural networks and DL uses what’s often the umbrella term of ANNs to solve complex problems. As we will see in the next section, much of the ecosystem that’s been formed in DL has been inspired by our own brains, where the “...

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