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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
Concepts
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Author (1):
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Irene Bratsis Irene Bratsis
Author Profile Icon Irene Bratsis
Irene Bratsis
LinkedIn
Irene Bratsis is a director of digital product and data at the International WELL Building Institute (IWBI). She has a bachelor's in economics and international relations from Simmons University. After completing various MOOCs in data science and big data analytics, she completed a data science apprentice program with Thinkful. Before joining IWBI, Irene worked as an operations analyst at Tesla, a data scientist at Gesture, a data product manager at Beekin, and head of product at Tenacity. Irene volunteers as NYC chapter co-lead for Women in Data, has coordinated various AI accelerators, moderated countless events with a speaker series with Women in AI called WaiTalk, and runs a monthly book club focused on data and AI books.
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Toc

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

Index

A

A/B testing 128

model deployment strategy 32, 33

tool selection considerations 239

adaptability manager 409

adaptive AI 305

adversarial models 20

agile development 161

AI4ALL 391

AI customization 141, 142

AI enablement 306

AI expert 399

AI, for commercial applications 109

examples 110, 111

product perspective 111

AI for commercial applications, use cases

art creation 110

ideation for sustainability 110

personalized AI companions 110

AI, for economic systems 102

examples and use cases 102, 103

limitations 104

product perspective 104, 105

AI for Good 116, 385

examples 116, 117

AI, for governmental sectors 112

use cases 112-114

AI for healthcare sector, use cases

drug discovery and development 106

healthcare for disabilities 107

hospital systems 106

mental health and suicide prevention 107

personal health monitoring 106

vision enhancement 107

...
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Authors (1)

Profile icon Irene Bratsis
Irene Bratsis
LinkedIn icon
Irene Bratsis is a director of digital product and data at the International WELL Building Institute (IWBI). She has a bachelor's in economics and international relations from Simmons University. After completing various MOOCs in data science and big data analytics, she completed a data science apprentice program with Thinkful. Before joining IWBI, Irene worked as an operations analyst at Tesla, a data scientist at Gesture, a data product manager at Beekin, and head of product at Tenacity. Irene volunteers as NYC chapter co-lead for Women in Data, has coordinated various AI accelerators, moderated countless events with a speaker series with Women in AI called WaiTalk, and runs a monthly book club focused on data and AI books.
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See other products by Irene Bratsis
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