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 DescriptionProduct 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.

Most economists agree that AI is a general purpose technology (GPT) like the steam engine, electricity, and the computer. AI will drive innovation in all sectors of the economy for the foreseeable future. Practical AI for Business Leaders, Product Managers, and Entrepreneurs is a technical guidebook for the business leader or anyone responsible for leading AI-related initiatives in their organization. The book can also be used as a foundation to explore the ethical implications of AI. Authors Alfred Essa and Shirin Mojarad provide a gentle introduction to foundational topics in AI. Each topic is framed as a triad: concept, theory, and practice. The concept chapters develop the intuition, culminating in a practical case study. The theory chapters reveal the underlying technical machinery. The practice chapters provide code in Python to implement the models discussed in the case study. With this book, readers will learn: The technical foundations of machine learning and deep learning How to apply the core technical concepts to solve business problems The different methods used to evaluate AI models How to understand model development as a tradeoff between accuracy and generalization How to represent the computational aspects of AI using vectors and matrices How to express the models in Python by using machine learning libraries such as scikit-learn, statsmodels, and keras

With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level upyour skills. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance. Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and more Use automated machine learning to implement a specific subset of use cases with SageMaker Autopilot Dive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, model training, and deployment Tie everything together into a repeatable machine learning operations pipeline Explore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache Kafka Learn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more

The missing manual on how to apply Lean Startup to build products that customers love The Lean Product Playbook is a practical guide to building products that customers love. Whether you work at a startup or a large, established company, we all know that building great products is hard. Most new products fail. This book helps improve your chances of building successful products through clear, step-by-step guidance and advice. The Lean Startup movement has contributed new and valuable ideas about product development and has generated lots of excitement. However, many companies have yet to successfully adopt Lean thinking. Despite their enthusiasm and familiarity with the high-level concepts, many teams run into challenges trying to adopt Lean because they feel like they lack specific guidance on what exactly they should be doing. If you are interested in Lean Startup principles and want to apply them to develop winning products, this book is for you. This book describes the Lean Product Process: a repeatable, easy-to-follow methodology for iterating your way to product-market fit. It walks you through how to: Determine your target customers Identify underserved customer needs Create a winning product strategy Decide on your Minimum Viable Product (MVP) Design your MVP prototype Test your MVP with customers Iterate rapidly to achieve product-market fit This book was written by entrepreneur and Lean product expert Dan Olsen whose experience spans product management, UX design, coding, analytics, and marketing across a variety of products. As a hands-on consultant, he refined and applied the advice in this book as he helped many companies improve their product process and build great products. His clients include Facebook, Box, Hightail, Epocrates, and Medallia. Entrepreneurs, executives, product managers, designers, developers, marketers, analysts and anyone who is passionate about building great products will find The Lean Product Playbook an indispensable, hands-on resource.

If you’re new to software product management or just want to learn more about it, there’s plenty of advice available—but most of it is geared toward consumer products. Creating high-quality software for the enterprise involves a much different set of challenges. In this practical book, two expert product managers provide straightforward guidance for people looking to join the thriving enterprise market. Authors Blair Reeves and Benjamin Gaines explain critical differences between enterprise and consumer products, and deliver strategies for overcoming challenges when building for the enterprise. You’ll learn how to cultivate knowledge of your organization, the products you build, and the industry you serve. Explore why: Identifying customer vs user problems is an enterprise project manager’s main challenge Effective collaboration requires in-depth knowledge of the organization Analyzing data is key to understanding why users buy and retain your product Having experience in the industry you’re building products for is valuable Product longevity depends on knowing where the industry is headed

Learn how Artificial Intelligence (AI) is being applied in the fashion industry. With an application focused approach, this book provides real-world examples, breaks down technical jargon for non-technical readers, and provides an educational resource for fashion professionals. The book investigates the ways in which AI is impacting every part of the fashion value chain starting with product discovery and working backwards to manufacturing. Artificial Intelligence for Fashion walks you through concepts, such as connected retail, data mining, and artificially intelligent robotics. Each chapter contains an example of how AI is being applied in the fashion industry illustrated by one major technological theme. There are no equations, algorithms, or code. The technological explanations are cumulative so you'll discover more information about the inner workings of artificial intelligence in practical stages as the book progresses. What You’ll Learn Gain a basic understanding of AI and how it is used in fashion Understand key terminology and concepts in AI Review the new competitive landscape of the fashion industry Conceptualize and develop new ways to apply AI within the workplaceWho This Book Is For Fashion industry professionals from designers, managers, department heads, and executives can use this book to learn about how AI is impacting roles in every department and profession.

Understand how to adopt and implement AI in your organizationKey Featuresa- 7 Principles of an AI Journeya- The TUSCANE Approach to Become Data Readya- The FAB-4 Model to Choose the Right AI Solutiona- Major AI Techniques & their Applications:- CART & Ensemble Learning- Clustering, Association Rules & Search- Reinforcement Learning- Natural Language Processing- Image RecognitionDescriptionMost AI initiatives in organizations fail today not because of a lack of good AI solutions, but because of a lack of understanding of AI among its end users, decision makers and investors. Today, organizations need managers who can leverage AI to solve business problems and provide a competitive advantage. This book is designed to enable you to fill that need, and create an edge for your career.The chapters offer unique managerial frameworks to guide an organization's AI journey. The first section looks at what AI is; and how you can prepare for it, decide when to use it, and avoid pitfalls on the way. The second section dives into the different AI techniques and shows you where to apply them in business. The final section then prepares you from a strategic AI leadership perspective to lead the future of organizations.By the end of the book, you will be ready to offer any organization the capability to use AI successfully and responsibly - a need that is fast becoming a necessity.What will you learna- Understand the major AI techniques & how they are used in business.a- Determine which AI technique(s) can solve your business problem.a- Decide whether to build or buy an AI solution.a- Estimate the financial value of an AI solution or company.a- Frame a robust policy to guide the responsible use of AI.Who this book is forThis book is for Executives, Managers and Students on both Business and Technical teams who would like to use Artificial Intelligence effectively to solve business problems or get an edge in their careers.Table of Contents1.Preface2.Acknowledgement3.About the Author4.Section 1: Beginning an AI Journeya. AI Fundamentalsb. 7 Principles of an AI Journeyc. Getting Ready to Use AI5.Section 2: Choosing the Right AI Techniquesa. Inside the AI Laboratoryb. How AI Predicts Values & Categoriesc. How AI Understands and Predicts Behaviors & Scenariosd. How AI Communicates & Learns from Mistakese. How AI Starts to Think Like Humans6.Section 3: Using AI Successfully & Responsiblya. AI Adoption & Valuationb. AI Strategy, Policy & Risk Management7.EpilogueAbout the AuthorsMalay A. Upadhyay is a Customer Journey executive, certified in Machine Learning. Over the course of his role heading the function at a N. American AI SaaS firm in Toronto, Malay trained 150+ N. American managers on the basics of AI and its successful adoption, held executive thought leadership sessions for CEOs and CHROs on AI strategy & IT modernization roadmaps, and worked as the primary liaison to realize AI value on unique customer datasets. It was here that he learnt the growing need for greater knowledge and awareness of how to use AI both responsibly and successfully.Malay was also one of 25 individuals chosen globally to envision the industrial future for the Marzotto Group, Italy, on its 175th anniversary. He holds an MBA, M.Sc. and B.E., with experiences across India, UAE, Italy and Canada.A Duke of Edinburgh awardee, Malay has been driving the subject of responsible AI management as an advisor, author, online instructor and member of the European AI Alliance that informed the HLEG on the European Commission's AI policy.