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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

Choosing your AI PM specialization

There are a number of paths that are available to you as an AI PM. Often, the main problem is just choosing one. Review Part 1 of this book when you’re deciding on this to better understand which areas of AI resonate with you most. This is a great starting point for many AI PMs because the area of AI you choose to predominantly focus on will be the area of AI you will invest in first. The following are a few questions to get you thinking in the right direction as you’re starting to build a career as an AI PM:

  • Are you most excited by supervised or unsupervised learning models?
  • Do you have a preference for deep learning or traditional ML?
  • Are you more interested in developing consumer-facing applications or enterprise solutions?
  • Which industries (such as healthcare, finance, retail, or transportation) do you find most intriguing?
  • What are your strongest technical skills (ML, natural language processing...
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