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The AI Product Manager's Handbook

You're reading from  The AI Product Manager's Handbook

Product type Book
Published in Feb 2023
Publisher Packt
ISBN-13 9781804612934
Pages 250 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Irene Bratsis Irene Bratsis
Profile icon 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 after completing various MOOCs in data science and big data analytics, she completed a data science 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.
See other products by Irene Bratsis

Table of Contents (19) Chapters

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 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

Sickness and health – the benefits of AI and nanotech across healthcare

AI continues to be incredibly successful when applied to the medical and healthcare industry. Drug discovery and development companies such as CytoReason, DeepCure, and BullFrog AI help their customers find and analyze new molecular compounds to create novel drugs for some of the most pressing illnesses that plague humanity, shorten time to market for these new drugs, and assist with the patenting process. Companies such as Standigm enable AI workflows to leverage AI through the journey of highly customizable target identification and lead generation. Before AI, the journey to discovering a new drug, conducting clinical trials, and bringing the drug to market might have taken upward of 10 years.

We also see personalization and prediction being applied to personal care through the use of AI, which is particularly exciting when you consider the doctor shortage we’re experiencing worldwide. Wouldn...

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Authors (1)

Profile icon 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 after completing various MOOCs in data science and big data analytics, she completed a data science 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.
Read more
See other products by Irene Bratsis

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