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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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Toc

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

Summary

The work of a PM is never done. There are always more voices, perspectives, and considerations to take in. Coordinating all the stakeholders, technology, leadership, market analysis, customer feedback, and passion for a product isn’t an easy task. In this chapter, we covered the stages of the AI product development life cycle and the various roles that can make up your AI product dream team. We also covered the tech stack that can help that team build a product, and various focus areas to help that product stand out and resonate with the cohorts of groups that will be buying and using your product. Hopefully, this chapter has helped you understand what the most important factors are when you set out to build an AI native product.

As long as you’re hiring the right people for the roles you have open in your AI program, doing your due diligence to uncover the right strategy for tech stack adoption, structuring your product in a way that benefits your customers...

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