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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

Irene Bratsis

NZ$68.99

Audiobook Feb 2023 9hrs 4mins 1st Edition

NZ$41.99 ~~NZ$46.99~~

Irene Bratsis

NZ$68.99

Audiobook Feb 2023 9hrs 4mins 1st Edition

NZ$41.99 ~~NZ$46.99~~

NZ$41.99 ~~NZ$46.99~~

What do you get with Audiobook?

Download a zip folder containing audio files (MP3) and a supplementary PDF

Access this title in our online player

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View table of contents

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

What do you get with Audiobook?

Download a zip folder containing audio files (MP3) and a supplementary PDF

Access this title in our online player

DRM FREE - Listen whenever, wherever and however you want

OR

Product Details

Publication date : Feb 28, 2023

Length: 9hrs 4mins

Edition : 1st

Language : English

ISBN-13 : 9781805129202

Category :

Data

Languages :

Concepts :

Artificial Intelligence

Table of Contents

26 Chapters

Part 1: Lay of the Land – Terms, Infrastructure, Types of AI, and Products Done Well

Part 1: Lay of the Land – Terms, Infrastructure, Types of AI, and Products Done Well

Understanding the Infrastructure and Tools for Building AI Products

Understanding the Infrastructure and Tools for Building AI Products

Getting the most out of this book – get to know your free benefits

Definitions – what AI is and is not

Introducing ML and DL

ML versus DL – understanding the difference

Learning paradigms in ML

LLMs, NLP, GANs, and generative AI

Succeeding in AI – how well-managed AI companies do infrastructure right

The order – what is the optimal flow and where does every part of the process live?

Storing and managing data

Managing projects – IaaS

Deployment strategies – what do we do with these outputs?

The promise of AI – where is AI taking us?

Additional resources

Join us on Discord

Model Development and Maintenance for AI Products

Model Development and Maintenance for AI Products

Understanding the stages of NPD

Model types – from linear regression to neural networks

Training – when is a model ready for market?

Deployment – what happens after training?

Testing and troubleshooting

Ethical retraining – the ethics of how often we update our models

Additional resources

Deep Learning Deep Dive

Deep Learning Deep Dive

Types of neural networks

Exploring generative AI models

Emerging technologies – ancillary and related tech

Explainability – optimizing for ethics, caveats, and responsibility

Guidelines for success

Commercializing AI Products

Commercializing AI Products

The professionals – examples of B2B products done right

The artists – examples of B2C products done right

The pioneers – examples of blue ocean products

The rebels – examples of red ocean products

The GOATs – examples of differentiated disruptive and dominant strategy products

Join us on Discord

AI Transformation and Its Impact on Product Management

AI Transformation and Its Impact on Product Management

Money and value – how AI could revolutionize our economic systems

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

Goods and services – growth in commercial applications

Government and autonomy – how AI will shape our borders and freedom

Basic needs – AI for Good

Additional resources

Part 2: Building an AI-Native Product

Part 2: Building an AI-Native Product

Understanding the AI-Native Product

Understanding the AI-Native Product

Stages of AI product development

AI/ML product dream team

Investing in your tech stack

Productizing AI-powered outputs – how AI product management is different

AI customization

Selling AI – product management as a higher octave of sales

Productizing the ML Service

Productizing the ML Service

Basics of productizing

AI versus traditional software product management

B2B versus B2C – productizing business models

Using AIOps/MLOps

Customization for Verticals, Customers, and Peer Groups

Customization for Verticals, Customers, and Peer Groups

Domains – orienting AI toward specific areas

Verticals – examination of some key domains

Thought leadership – learning from peer groups

Join us on Discord

Product Design for the AI-Native Product

Product Design for the AI-Native Product

Product design elements 101

What makes the AI-native product design process special?

Choosing your priorities wisely

What’s the story you’re telling?

Benchmarking Performance, Growth Hacking, and Cost

Benchmarking Performance, Growth Hacking, and Cost

Value metrics – a guide to north star metrics, KPIs and OKRs

Hacking – product-led growth

The tech stack – early signals

Managing costs and pricing – AI is expensive

Join us on Discord

Managing the AI-Native Product

Managing the AI-Native Product

The head – Managing alignment

The heart – Managing people and values

The guts – Managing the rest

Join us on Discord

Part 3: Integrating AI into Existing Traditional Software Products

Part 3: Integrating AI into Existing Traditional Software Products

The Rising Tide of AI

The Rising Tide of AI

Evolve or die – when change is the only constant

Changes in the Fourth Industrial Revolution

Fear is not the answer – there is more to gain than lose (or spend)

Anticipating potential risks

How LLMs are evolving and the rise of open source LLM capabilities

Trends and Insights Across Industry

Trends and Insights Across Industry

Highest growth areas for AI integration

Low-hanging fruit – quickest wins for AI enablement

Riding the GenAI wave

Evolving Products into AI Products

Evolving Products into AI Products

Ideation – what’s possible, what’s desirable, and what’s probable

Data management – the bloodstream of the company

Competition – love your enemies

Product strategy – building a blueprint that works for everyone

Red flags and green flags – what to look for and watch out for

Additional resources

Join us on Discord

The Role of AI Product Design

The Role of AI Product Design

The evolution of product design

Expansion: What makes the evolved AI product special?

Choosing your words carefully

Building with trust and security

Managing the Evolving AI Product

Managing the Evolving AI Product

The head – managing alignment

The heart – managing the people and values

The guts – managing data, infrastructure, and ongoing maintenance

Join us on Discord

Part 4: Managing the AI PM Career

Part 4: Managing the AI PM Career

Starting a Career as an AI PM

Starting a Career as an AI PM

Bolstering your knowledge in theory and practice

What an AI PM looks like today

The importance of communities

Choosing your AI PM specialization

What Does It Mean to Be a Good AI PM?

What Does It Mean to Be a Good AI PM?

A job family of many hats

The AI whisperer and the role of communicating accessibly

Common challenges and opportunities as you’re leveling up in your career

The importance of self-care

Maturing and Growing as an AI PM

Maturing and Growing as an AI PM

Projecting – what’s your ideal AI PM roadmap?

Learning – staying informed and inspired

Networking – deepening your involvement with the professional community

Growing – the student becomes the teacher

What’s next? The world is our oyster

Unlock Your Book’s Exclusive Benefits

Unlock Your Book’s Exclusive Benefits

How to unlock these benefits in three easy steps

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About the author

Irene Bratsis

Irene Bratsis

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.

See other products by Irene Bratsis

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