These are book recommendations for leaders and practitioners. I only recommend books I’ve personally read, reviewed, or used over the years. While you might feel these books are old and irrelevant, they’re really not.
Many of the concepts that we have today are built on these foundational concepts. From my experience, having a good foundation and breadth of knowledge in machine learning will make you a more well-informed practitioner and leader.
For Business Leaders
Artificial Intelligence by Melanie Mitchell
Why is this book recommended?
If you want more technical depth in AI, but not so technical that you can’t follow along, try this book. It covers the basics of AI while also providing a historical perspective on AI, but it doesn’t cover Gen AI. Melanie makes it intuitive to follow and weaves in interesting stories throughout.
Melanie is a highly accomplished computer science researcher and professor; you may have to do some abstraction of knowledge to apply her perspective to the business context.
Empire of AI by Karen Hao
Why is this book recommended?
Maybe you don’t like gossip, but maybe you do. As controversial as this book is, it is recommended to help you understand that there are power dynamics in AI. This can significantly affect the decisions businesses make in AI models they invest in and companies they will or will not work with. Reading other perspectives will help you form your own, and you will make better business decisions as a leader.
Caution: the book’s reporting may seem overly one-sided, opinionated, and negative.
AI at the Edge by Daniel Situnayake & Jenny Plunkett
Why is this book recommended?
We keep talking about LLMs, but rarely talk about AI at the edge, where we execute AI tasks directly on local devices, such as smartphones, tablets, or a local server, instead of sending data to a remote cloud for processing.
There are a considerable number of real-world applications for AI at the edge. This book offers interesting real-world examples and best practices for implementing AI, both in general and on devices. If you’re a practitioner, read all the way through. For leaders: even if you read the first few chapters of the book, it will spark ideas.
For Practitioners
Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norvig
Why is this book recommended?
If you really want to go deep into the weeds of AI, not necessarily from the points of view of modern AI, but from a foundational perspective, then this book is a classic. It can be hard to read and understand at times, but tackling it in small chunks can be helpful. It’s authored by the best of the best in the field, so try to extract what you can to improve your foundational knowledge.
The Hundred-Page Machine Learning Book By Andriy Burkov
Why is this book recommended?
For a quick review of machine learning concepts, this book is a good choice. If you’re preparing for interviews or if you want to brush up on concepts, this book gives a breadth of knowledge communicated concisely. Note that the focus is traditional AI only (e.g., clustering, linear regression, etc). There’s another book by this author focused on LLMs. But I haven’t personally reviewed it.