9 Best Books on Machine Learning and AI for Product Managers
Artificial intelligence, deep learning, and machine learning are not just buzzwords, but topics that take up a good amount of time in a Product Manager's job. We leverage them to enhance, improve, create, and shape our products in all possible ways. Most companies are nowadays also staffed with Machine Learning specialists and Data scientists to help Product teams create new and better experiences for their customers. We've collected our nine favorite books that will help you get familiar or further deep-dive into the topic of AI and ML.
Competing in the Age of AI
Why read?
“A provocative new book” – The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning–to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how “collisions” between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples–including many from the most powerful and innovative global, AI-driven competitors–and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI.
288 pages, 2020
Data Science for Business
Why read?
Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science and walks you through the “data-analytic thinking” necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. “A must-read resource for anyone who is serious about embracing the opportunity of big data.” — Craig Vaughan, Global Vice President at SAP
414 pages, 2013
AI Superpowers
Why read?
Nobody understands the complexity of issues that will drive the explosive development of artificial intelligence in China and the U.S. better than Kai-Fu Lee. He is a technical wizard who has led AI research and development teams in both countries, has lived in both cultures, and today operates one of the most prominent AI venture funds in China. His insights into the diverse cultural, governmental and technical factors that will frame the competition between nations make this book a must-read for anybody interested in the future of AI, and how it might change the world order.
272 pages, 2018
HBR's 10 Must Reads on AI, Analytics, and the New Machine Age
Why read?
Intelligent machines are revolutionizing business. Machine learning and data analytics are powering a wave of groundbreaking technologies. Is your company ready? If you read nothing else on how intelligent machines are revolutionizing business, read these 10 articles. We’ve combed through hundreds of Harvard Business Review articles and selected the most important ones to help you understand how these technologies work together, how to adopt them, and why your strategy can’t ignore them. In this book you’ll learn how: Data science, driven by artificial intelligence and machine learning, is yielding unprecedented business insights Blockchain has the potential to restructure the economy Drones and driverless vehicles are becoming essential tools 3-D printing is making new business models possible Augmented reality is transforming retail and manufacturing Smart speakers are redefining the rules of marketing Humans and machines are working together to reach new levels of productivity This collection of articles includes “Artificial Intelligence for the Real World,” by Thomas H. Davenport and Rajeev Ronanki; “Stitch Fix’s CEO on Selling Personal Style to the Mass Market,” by Katrina Lake; “Algorithms Need Managers, Too,” by Michael Luca, Jon Kleinberg, and Sendhil Mullainathan; “Marketing in the Age of Alexa,” by Niraj Dawar; “Why Every Organization Needs an Augmented Reality Strategy,” by Michael E. Porter and James E. Heppelmann; “Drones Go to Work,” by Chris Anderson; “The Truth About Blockchain,” by Marco Iansiti and Karim R. Lakhani; “The 3-D Printing Playbook,” by Richard A. D’Aveni; “Collaborative Intelligence: Humans and AI Are Joining Forces,” by H. James Wilson and Paul R. Daugherty; “When Your Boss Wears Metal Pants,” by Walter Frick; and “Managing Our Hub Economy,” by Marco Iansiti and Karim R. Lakhani.
192 pages, 2019
Prediction Machines
Why read?
In Prediction Machines, three eminent economists recast the rise of AI as a drop in the cost of prediction. With this single, masterful stroke, they lift the curtain on the AI-is-magic hype and show how basic tools from economics provide clarity about the AI revolution and a basis for action by CEOs, managers, policymakers, investors, and entrepreneurs. “What does AI mean for your business? Read this book to find out.” — Hal Varian, Chief Economist, Google
250 pages, 2018
The Master Algorithm
Why read?
A spell-binding quest for the one algorithm capable of deriving all knowledge from data, including a cure for cancer Society is changing, one learning algorithm at a time, from search engines to online dating, personalized medicine to predicting the stock market. But learning algorithms are not just about Big Data - these algorithms take raw data and make it useful by creating more algorithms. This is something new under the sun: a technology that builds itself. In The Master Algorithm, Pedro Domingos reveals how machine learning is remaking business, politics, science and war. And he takes us on an awe-inspiring quest to find ‘The Master Algorithm’ - a universal learner capable of deriving all knowledge from data.
352 pages, 2015
Data Science for Executives
Why read?
Leaders don’t have to be scientists to unlock the power of AI technology that is already radically altering the industrial landscape. If you’re ready to meet the challenges of this new revolution, this essential guide will help you take your business to the next level.
184 pages, 2018
Applied Artificial Intelligence
Why read?
Applied Artificial Intelligence is a practical guide for business leaders who are passionate about leveraging machine intelligence to enhance the productivity of their organizations and the quality of life in their communities. If you want to drive innovation by combining data, technology, design, and people to solve real problems at an enterprise scale, this is your playbook.
175 pages, 2018
Designing Agentive Technology
Why read?
Advances in narrow artificial intelligence make possible agentive systems that do things directly for their users (like, say, an automatic pet feeder). They deliver on the promise of user-centred design, but present fresh challenges in understanding their unique promises and pitfalls. Designing Agentive Technology provides both a conceptual grounding and practical advice to unlock agentive technology’s massive potential. All rights reserved Talks at Google
240 pages, 2017