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The AI product manager's handbook : develop a product that takes advantage of machine learning to solve AI problems /
Master the skills required to become an AI product manager and drive the successful development and deployment of AI products to deliver value to your organization. Purchase of the print or Kindle book includes a free PDF eBook. Key Features Build products that leverage AI for the common good and co...
| Clasificación: | Libro Electrónico |
|---|---|
| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham, UK :
Packt Publishing Ltd.,
2023.
|
| Edición: | 1st edition. |
| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
MARC
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| 100 | 1 | |a Bratsis, Irene, |e author. | |
| 245 | 1 | 4 | |a The AI product manager's handbook : |b develop a product that takes advantage of machine learning to solve AI problems / |c Irene Bratsis. |
| 246 | 3 | |a Artificial intelligence product manager's handbook | |
| 250 | |a 1st edition. | ||
| 264 | 1 | |a Birmingham, UK : |b Packt Publishing Ltd., |c 2023. | |
| 300 | |a 1 online resource (250 pages) : |b illustrations | ||
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| 500 | |a Includes index. | ||
| 520 | |a Master the skills required to become an AI product manager and drive the successful development and deployment of AI products to deliver value to your organization. Purchase of the print or Kindle book includes a free PDF eBook. Key Features 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 Book 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. 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 Who this book is 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. | ||
| 505 | 0 | |a Cover -- Title Page -- Copyright and Credits -- Dedication -- Contributors -- Table of Contents -- Preface -- Part 1 -- Lay of the Land -- Terms, Infrastructure, Types of AI, and Products Done Well -- Chapter 1: Understanding the Infrastructure and Tools for Building AI Products -- Definitions -- what is and is not AI -- ML versus DL -- understanding the difference -- ML -- DL -- Learning types in ML -- Supervised learning -- Unsupervised learning -- Semi-supervised learning -- Reinforcement learning -- The order -- what is the optimal flow and where does every part of the process live? | |
| 505 | 8 | |a Step 1 -- Data availability and centralization -- Step 2 -- Continuous maintenance -- Database -- Data warehouse -- Data lake (and lakehouse) -- Data pipelines -- Managing projects -- IaaS -- Deployment strategies -- what do we do with these outputs? -- Shadow deployment strategy -- A/B testing model deployment strategy -- Canary deployment strategy -- Succeeding in AI -- how well-managed AI companies do infrastructure right -- The promise of AI -- where is AI taking us? -- Summary -- Additional resources -- References -- Chapter 2: Model Development and Maintenance for AI Products | |
| 505 | 8 | |a Understanding the stages of NPD -- Step 1 -- Discovery -- Step 2 -- Define -- Step 3 -- Design -- Step 4 -- Implementation -- Step 5 -- Marketing -- Step 6 -- Training -- Step 7 -- Launch -- Model types -- from linear regression to neural networks -- Training -- when is a model ready for market? -- Deployment -- what happens after the workstation? -- Testing and troubleshooting -- Refreshing -- the ethics of how often we update our models -- Summary -- Additional resources -- References -- Chapter 3: Machine Learning and Deep Learning Deep Dive -- The old -- exploring ML -- The new -- exploring DL | |
| 505 | 8 | |a Invisible influences -- A brief history of DL -- Types of neural networks -- Emerging technologies -- ancillary and related tech -- Explainability -- optimizing for ethics, caveats, and responsibility -- Accuracy -- optimizing for success -- Summary -- References -- Chapter 4: 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 GOAT -- examples of differentiated disruptive and dominant strategy products | |
| 505 | 8 | |a The dominant strategy -- The disruptive strategy -- The differentiated strategy -- Summary -- References -- Chapter 5: AI Transformation and Its Impact on Product Management -- Money and value -- how AI could revolutionize our economic systems -- Goods and services -- growth in commercial MVPs -- Government and autonomy -- how AI will shape our borders and freedom -- Sickness and health -- the benefits of AI and nanotech across healthcare -- Basic needs -- AI for Good -- Summary -- Additional resources -- References -- Part 2 -- Building an AI-Native Product | |
| 590 | |a O'Reilly |b O'Reilly Online Learning: Academic/Public Library Edition | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Product management. | |
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| 650 | 7 | |a Product management. |2 fast |0 (OCoLC)fst01078225 | |
| 776 | 0 | 8 | |i Print version: |a Bratsis, Irene |t The the AI Product Manager's Handbook |d Birmingham : Packt Publishing, Limited,c2023 |z 9781804612934 |
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