AI product manager's handbook

• Verfasst von: Bratsis, Irene [VerfasserIn]
• Titel: AI product manager's handbook
• Titelzusatz: build, integrate, scale, and optimize products to grow as an AI product manager
• Verf.angabe: Irene Bratsis
• Ausgabe: Second edition.
• Verlagsort: Birmingham, UK
• Verlag: Packt Publishing Ltd.
• Jahr: 2024
• Umfang: 1 online resource (484 pages)
• Illustrationen: illustrations
• Gesamttitel/Reihe: Expert insight
• Fussnoten: Includes bibliographical references and index
• ISBN: 978-1-83588-284-9
• Datenträger: Online-Ressource
• Sprache: eng
• Sach-SW: Intelligence artificielle
• Sach-SW: Produits commerciaux ; Gestion
• Sach-SW: artificial intelligence
• K10plus-PPN: 1914058429
• K10plus-PPN:
  Universitätsbibliothek
• Lokale URL UB: Zum Volltext
• Lokale URL UB: Bibliothek der Medizinischen Fakultät Mannheim der Universität Heidelberg
• Bibliothek/Idn: UW / m464821515X
• Lokale URL Inst.: Zum Volltext

Abstract

This book will provide you with a detailed roadmap for successfully building, maintaining, and evolving artificial intelligence (AI)-driven products, serving as an indispensable companion on your journey to becoming an effective AI PM. We'll explore the AI landscape, demystify complex terms, and walk you through infrastructure, algorithms, and deployment strategies. You'll master essential skills to understand the optimal flow of AI processes, learn about the product development life cycle from ideation to deployment, and familiarize yourself with commonly used model development techniques. We'll discuss the intricacies of building products natively with AI, as well as evolving traditional software product to AI products. Regardless of your use case, we'll show you how you can craft compelling stories to captivate your audience. We'll help you find the right balance between foundational product design elements and the unique aspects of managing AI products, so you can prioritize wisely. We'll also explore career considerations for AI PMs. By the end of this book, you will understand the importance of AI integration and be able to explore emerging AI/ML models like Generative AI and LLMs. You'll discover open-source capabilities and best practices for ideating, building, and deploying AI products across verticals.