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The AI Product Manager's Handbook
The AI Product Manager's Handbook

The AI Product Manager's Handbook: Develop a product that takes advantage of machine learning to solve AI problems

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Key benefits

  • Build products that leverage AI for the common good and commercial success
  • Take macro data and use it to show your customers you’re a source of truth
  • Best practices and common pitfalls that impact companies while developing AI product

Description

Product managers working with artificial intelligence will be able to put their knowledge to work with this practical guide to applied AI. This book covers everything you need to know to drive product development and growth in the AI industry. From understanding AI and machine learning to developing and launching AI products, it provides the strategies, techniques, and tools you need to succeed. The first part of the book focuses on establishing a foundation of the concepts most relevant to maintaining AI pipelines. The next part focuses on building an AI-native product, and the final part guides you in integrating AI into existing products. You’ll learn about the types of AI, how to integrate AI into a product or business, and the infrastructure to support the exhaustive and ambitious endeavor of creating AI products or integrating AI into existing products. You’ll gain practical knowledge of managing AI product development processes, evaluating and optimizing AI models, and navigating complex ethical and legal considerations associated with AI products. With the help of real-world examples and case studies, you’ll stay ahead of the curve in the rapidly evolving field of AI and ML. By the end of this book, you’ll have understood how to navigate the world of AI from a product perspective.

Who is this book for?

This book is for product managers and other professionals interested in incorporating AI into their products. Foundational knowledge of AI is expected. If you understand the importance of AI as the rising fourth industrial revolution, this book will help you surf the tidal wave of digital transformation and change across industries.

What you will learn

  • Build AI products for the future using minimal resources
  • Identify opportunities where AI can be leveraged to meet business needs
  • Collaborate with cross-functional teams to develop and deploy AI products
  • Analyze the benefits and costs of developing products using ML and DL
  • Explore the role of ethics and responsibility in dealing with sensitive data
  • Understand performance and efficacy across verticals

Product Details

Country selected
Publication date, Length, Edition, Language, ISBN-13
Publication date : Feb 28, 2023
Length: 9hrs 4mins
Edition : 1st
Language : English
ISBN-13 : 9781805129202
Category :
Languages :

What do you get with Audiobook?

Product feature icon Download a zip folder containing audio files (MP3) and a supplementary PDF
Product feature icon Access this title in our online player
Product feature icon DRM FREE - Listen whenever, wherever and however you want

Product Details

Publication date : Feb 28, 2023
Length: 9hrs 4mins
Edition : 1st
Language : English
ISBN-13 : 9781805129202
Category :
Languages :

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Table of Contents

18 Chapters
Part 1 – Lay of the Land – Terms, Infrastructure, Types of AI, and Products Done Well Chevron down icon Chevron up icon
Chapter 1: Understanding the Infrastructure and Tools for Building AI Products Chevron down icon Chevron up icon
Chapter 2: Model Development and Maintenance for AI Products Chevron down icon Chevron up icon
Chapter 3: Machine Learning and Deep Learning Deep Dive Chevron down icon Chevron up icon
Chapter 4: Commercializing AI Products Chevron down icon Chevron up icon
Chapter 5: AI Transformation and Its Impact on Product Management Chevron down icon Chevron up icon
Part 2 – Building an AI-Native Product Chevron down icon Chevron up icon
Chapter 6: Understanding the AI-Native Product Chevron down icon Chevron up icon
Chapter 7: Productizing the ML Service Chevron down icon Chevron up icon
Chapter 8: Customization for Verticals, Customers, and Peer Groups Chevron down icon Chevron up icon
Chapter 9: Macro and Micro AI for Your Product Chevron down icon Chevron up icon
Chapter 10: Benchmarking Performance, Growth Hacking, and Cost Chevron down icon Chevron up icon
Part 3 – Integrating AI into Existing Non-AI Products Chevron down icon Chevron up icon
Chapter 11: The Rising Tide of AI Chevron down icon Chevron up icon
Chapter 12: Trends and Insights across Industry Chevron down icon Chevron up icon
Chapter 13: Evolving Products into AI Products Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon
Other Books You May Enjoy Chevron down icon Chevron up icon

Customer reviews

Most Recent
Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.5
(28 Ratings)
5 star 78.6%
4 star 7.1%
3 star 7.1%
2 star 0%
1 star 7.1%
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Vanessa Merck Jul 21, 2024
Full star icon Empty star icon Empty star icon Empty star icon Empty star icon 1
Geht nicht auf die Neuerungen durch LLMs wie Chat-GPT ein. Nur Basis Wissen zu allgemeiner KI. Nicht zu empfehlen.Autoren mit mehr Kompetenz wären wünschenswert.
Amazon Verified review Amazon
Tenacious1976 Jul 02, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
As a pretty new product manager and as part of a team that is really focused on AI, I was keen to pick this up and get some deeper insights into working with AI as a product manager. This book stands out for its practical approach, demystifying complex machine learning concepts and offering actionable insights that bridge the gap between technical teams and product managers.One of the book's strongest points is its structured roadmap, which walks readers through the entire AI product lifecycle—from ideation and feasibility analysis to development and post-launch iterations. It effectively highlights the importance of collaboration between data scientists, engineers, and product managers, providing tools and frameworks to facilitate seamless communication and project alignment.Moreover, the case studies included are particularly enlightening, showcasing real-world applications of AI and the challenges encountered. These examples not only illustrate successful implementations but also provide valuable lessons from less successful attempts, making it a well-rounded educational resource.While the book is rich in detail, it remains accessible to those who may not have a deep technical background. The author's ability to explain machine learning principles in a clear and concise manner ensures that readers of varying expertise can grasp and apply the concepts.
Amazon Verified review Amazon
Ned Thompson May 31, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Well written as it went into great depth on AI and its influence on a product's development. With AI being such a hot topic, it was great to see it put in perspective and the eventual influence AI will have on product development and management in the future. Really appreciate that this book cuts through all the talk and focuses on important aspects.
Amazon Verified review Amazon
A. Nog. Mar 18, 2024
Full star icon Full star icon Full star icon Full star icon Empty star icon 4
Great resource for AI POs. Entire book I received has print quality issues though: entire paragraphs cut off or missing.
Amazon Verified review Amazon
Kam F Siu Jan 30, 2024
Full star icon Full star icon Full star icon Empty star icon Empty star icon 3
Feefo Verified review Feefo
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