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The AI Product Manager's Handbook

The AI Product Manager's Handbook

By : Irene Bratsis
4.6 (28)
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The AI Product Manager's Handbook

The AI Product Manager's Handbook

4.6 (28)
By: Irene Bratsis

Overview of this book

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.
Table of Contents (19 chapters)
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1
Part 1 – Lay of the Land – Terms, Infrastructure, Types of AI, and Products Done Well
7
Part 2 – Building an AI-Native Product
13
Part 3 – Integrating AI into Existing Non-AI Products

Model Development and Maintenance for AI Products

In this chapter, we will be exploring the nuances of model development, from linear regression to deep learning neural network models. We’ll cover the variety of models that are available to use, as well as what’s entailed for the maintenance of those models, from how they’re developed and trained to how they’re deployed and ultimately tested. This will be a basic overview to understand the end-to-end process of model maintenance that product managers can expect from the engineering and dev ops teams that support their products.

There’s a lot involved with bringing any new product to market, and if you’ve been a product manager for a while, you’re likely familiar with the new product development (NPD) process – or set of steps. As a precursor to the rest of the chapter, particularly for those that are unfamiliar with the NPD process, we’re going to be summarizing each...

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The AI Product Manager's Handbook
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