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This article showcases our top picks for the Best AI Books For Beginners. We reached out to industry leaders and experts who have contributed the suggestions within this article (they have been credited for their contributions below).
We are keen to hear your feedback on all of our content and our comment section is a moderated space to express your thoughts and feelings related (or not) to this article This list is in no particular order.
This product was recommended by Kristina Libby from SoCu
This book is a great way to get a lot of depth on the topic of AI from a number of different points of view at once. It talks about AI uses across education, manufacturing and more while also diving into ethics, accountability and politics. I think of it as a great primer for people who want to learn a lot at once and can use this to figure out which areas or topics they want to dive further into.
This is the book I’ve been waiting for, one that provides an intelligent summary of the current issues in Artificial Intelligence while managing to be accessible to a wide range of readers. This is AI demystified, a masterful overview in which Mitchell manages to address the entire field, from history and philosophy, examining the real accomplishments as well as describing what’s left to do. It’s surprising how many books are written about AI by people who don’t really know what it is or how it works. Not so here; after finishing this book, you will know what AI is about and why it’s getting attention these days.
We’ve been learning a lot about the power and reach of artificial intelligence–often referred to as AI–and how it is affecting our lives, jobs, and future. Even though the future will be exciting with more opportunities than ever before, most people are still concerned about some of the outcomes. This book addresses those concerns by offering 101 questions frequently asked about AI and deep learning, along with easy-to-understand answers you won’t find anywhere else. Packed with valuable insights and examples, this book helps you think about the impact this technology will have on almost every aspect of our lives.
Aurélien Géron, Senior AI Engineer, author of the bestseller Hands-On Machine Learning with Scikit-Learn and TensorFlow: The breadth of topics the book covers is amazing for just 100 pages (plus few bonus pages!). Burkov doesn’t hesitate to go into the math equations: that’s one thing that short books usually drop. I really liked how the author explains the core concepts in just a few words. The book can be very useful for newcomers in the field, as well as for old-timers who can gain from such a broad view of the field.
PixInsight has taken the astro-imaging world by storm. As the first comprehensive postprocessing platform to be created by astro-imagers for astro-imagers, it has for many replaced other generic graphics editors as the software of choice. PixInsight has been embraced by professionals such as the James Webb (and Hubble) Space Telescope’s science imager Joseph DePasquale and Calar Alto’s Vicent Peris, as well as thousands of amateurs around the world. While PixInsight is extremely powerful, very little has been printed on the subject. The first edition of this book broke that mold, offering a comprehensive look into the software’s capabilities. This second edition expands on the several new processes added to the PixInsight platform since that time, detailing and demonstrating each one with a now-expanded workflow. Addressing topics such as PhotometricColorCalibration, Large-Scale Pixel Rejection, LocalNormalization and a host of other functions, this text remains the authoritative guide to PixInsight.