According to experts, there are a handful of excellent books worth reading about Artificial Intelligence (AI), from popular interest to its practical applications. These are the best reads if you're remotely interested in the subject and want to learn more about this cutting-edge technology.
AI is constantly evolving, so users in the field must make it a constant priority to stay up to date with the latest developments and how the tech can be applied.
A panel of AI experts and authors, including AI consultant and author of the book entitled AI for People and Business: A Framework for Better Human Experiences and Business Success, Alex Castrounis, along with the founder of Guild AI, an open-source machine-learning (ML) engineering application, and CEO of an ML-powered recommendation engine, Jana Eggers, have all suggested a variety of important, insightful, and relevant AI books worth reading.
Their book choices range from a historical overview of machine learning to the more technical issue of what has become known in artificial intelligence as the black box problem, from a reflective review of algorithm bias to the fascination with AI's deep learning.
In other words, there's something for everyone, from informative and approachable books for technical and non-technical readers to the more advanced books about AI.
Let's dive straight in to discover today's best AI books without further ado.
AI Books That Focus on Deep Learning
Deep Learning by Ian Goodfellow, Yoshua Bengio, and Aaron Courville
This book discusses the basics of machine learning and is one of the best books ever written about deep learning. It has been penned in an extremely accessible way and is jam-packed with lots of useful information. However, it's also more technical than other books covering similar material, so some readers may find it too heavy. Nonetheless, it's still a great read and highly recommended.
Having a background in mathematics is important if you want to get to grips with the topics covered in this advanced textbook. It's the kind of book that's likely to be studied in a graduate-level course. After reading this one from back to front, some of you will take something away from this book, whereas others may find some parts more difficult to understand and won't be able to take much away. This book is available for purchase on Amazon.
Neural Networks and Deep Learning by Michael Nielson
This book focuses on deep learning and neural networks. It's much easier to read, and the concepts discussed are easier to grasp. Useful images, a small number of videos, and images also make this book more accessible to anyone wanting to learn more about this particular field in artificial intelligence. The author's voice and writing style are relatable, making the complex subject matter easier to understand.
Everyone learns in a different way, and some books have the ability to convey what they are trying to teach much better than others. However, this book has a much broader appeal, and most people with varying learning styles should be able to take something from this book thanks to its casual style. You can read this book for free here on the Neural Networks and Deep Learning website.
Rebooting AI: Building Artificial Intelligence We Can Trust by Gary Marcus and Ernest Davis
This book has many discussions about the deep learning of AI, and it will easily sit well with most people in this field. It gets us to take a closer look at artificial intelligence, the end game, and how it can benefit us the most. It then makes us question how important AI's deep learning capabilities are in our aspirations for the technology.
In short, the book points out that it can help us get where we need to be, but in other ways, it's not helpful in the slightest. It also highlights how the effort being put into deep learning is taking the attention away from other important areas that could be more beneficial. The book attempts to give the reader a different perspective of AI, taking us back to the more traditional AI disciplines and camps, of which there are several different ones.
It also takes us back to the basics of artificial intelligence, some of which is nearly half a century old and remains a key starting point for the continued advancement of the AI field. It's a great book because it offers a more laid-back review of the complexity of deep learning. Rebooting AI is available in many formats here on Amazon.com.
The Master Algorithm: How the Quest for The Ultimate Learning Machine Will Remake Our World By Pedro Domingos
Deep learning is one of the hottest topics in the field of artificial intelligence right now, and this book discusses the various camps, or tribes as this book's author refers to them, and the importance of understanding that a combination of systems will no doubt be the future of deep learning, instead of just one type of rules above all others.
Although, in most cases, tribes don't mix very well with each other, the book hints at how we need to encourage them to mix more often. An example is what DeepMind did with AlphaGo, which is a combination of up to three tribes. The book is aimed at those who are more technically minded and should teach them a thing or two about AI.
However, it has also been written clearly and concisely and is designed to help other less technically-minded people in business. People shouldn't be put off reading it, thinking it might be too technical to understand. The book is a great starting point for those wanting to educate themselves about deep learning. You can purchase this book on Amazon today.
Advanced AI Books
Interpretable Machine Learning by Christoph Molar
This is another technical book about AI deep learning that can also be likened to a textbook. It can also be described as a kind of guide for explaining the complex world of black boxes. The more you learn, the more difficult some of the subject matter of this book becomes. It is designed to help you understand your models, why they come up with the predictions they do, and why they are doing what they're doing.
Although AI has many benefits and a lot of potential, it also comes with several risks, depending on how you use it. It looks at how, as AI develops, transparency and interpretability themes will also arise, making us tread cautiously before advancing too quickly with artificial intelligence. One of the ways to do this is using more science data and mathematics.
Many papers cover black boxes, but hardly any books are like this one, which is why this book is an important read. Purchase this book here on Amazon.
Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech by Sara Wachter-Boettcher
This is another great book to learn more about advanced artificial intelligence. It's about understanding the bias and problems that can be created with certain algorithms. Only a couple of great books covering this subject are available, one of which is this one by Sara Wachter-Boettcher.
She offers plenty of different examples regarding technology and what's happening with digital transformation. Concerning some bias, one of the main issues she presents is that the data already comes with the bias built in. Even if you don't input specific bias tags, like race and gender or any other bias, there's already too much that's naturally built into systems because of what human bias already thinks.
Artificial intelligence can pick up on generalizations made by humans, which is why we must be careful about what information and data we feed it. How do we ensure we know what's going on, even when it's not obvious? If you're interested in purchasing this book you can do so by visiting here.
Accelerate: The Science of Lean Software and DevOps: Building and Scaling High Performing Technology Organizations by Nicole Forsgren, Jez Humble and Gene Kim
This book is about delivering the best possible product as a team and then repeatedly delivering the same great product. This is particularly crucial for artificial intelligence because you are subject to constant changes from both the algorithm and the data. The development of software has now transformed from being released every year to continuous deployment, and more people than ever are currently at this level of progress.
We also have to move quicker because the rapidly evolving algorithms can greatly impact the technology and software surrounding them. The data fed into systems is constantly changing, which changes the data models, and it's this data that impacts artificial intelligence the most. This is a far more complex ecosystem to deal with, so adopting certain principles is important. Some have likened it to DevOps on overdrive or hectic DevOps.
This book is, therefore, extremely important for artificial intelligence. Another book called Inspired, which we will look at further down, acts as a foundation, but this book is vital and the next logical step if you really need to deliver AI properly. The two books complement each other and are essential for artificial intelligence because AI is far more imprecise. It's important to get these definitions and deliveries down. Click here if you're interested to purchase this book.
Artificial intelligence books focused on ML
Machine Learning Yearning by Andrew Ng
In this book, which is great for practitioners, machine learning and how it applies to AI is broadly covered. However, it takes more of a how-to approach. It's kind of like, if this is what you want to do, this is how you should do it, and if you want to do that, this is how it should be done, and so on.
The book has also been laid out in a logical way that thoroughly replicates the process, trade-offs, and important factors that ML engineers and data scientists follow when undertaking ML projects from start to finish. In that respect, the book is rather unique and written by a person who is clearly at the forefront of this particular field. This book is available for free as a PDF you can download here.
The Hundred-Page Machine Learning Book by Andriy Burkov
This book has been written specifically for practitioners and provides a superb outline of ML, covering just about every key area of the machine learning field. Without being too technical or thoroughly mathematical, it includes a healthy amount of mathematics and theory. It's one book that all ML practitioners should have in their collection.
However, it's also an ideal read for non-practitioners who are simply looking to learn the numerous basic aspects of ML. It's extremely concise and sums up almost everything you need to know about machine learning. Although it's largely focused more towards the practitioner, it's ideal for anyone who wants to get to grips with the inner workings of ML.
Most chapters are around the same length, with each topic neatly summarized for you, including the important maths behind it, without going too deep into the complex equations. It's a great book you should consider adding to your collection. If you're interested in purchasing this book you can do you on Amazon by going here.
AI Books that are approachable for non-technical readers
How The Mind Works by Steven Pinker
Although this book isn't primarily focused on artificial intelligence, it does feature a small section on building AI. It has a comprehensive outlook on the evolutionary effect on our brain. It offers a unique take on how the human brain works, and AI is briefly mentioned in there. In short, it's a fantastic read worth checking out. Buy on Amazon.
Inspired: How to Create Tech Products Customers Love by Marty Cagan
This book was mentioned further up, and it's also not specifically centred on artificial intelligence. It's still an essential read for everyone from management to engineers. It also helps people understand each other's roles more.
The author has come up with a good outline for how people can characterize and deliver their products. Although the info in this book can be applied to all products in general, the focus is more towards technical products. Plus, it's a relatively quick read.
If you have a few spare hours with nothing to do, you can flick through it and still retain plenty of useful information. Cagan has been in the industry for many years, and the knowledge he shares in his book is invaluable. Buy this book here on Amazon.
AI For People and Business by Alex Castrounis
It has never been more important than it is today for business owners to have a good understanding of AI and ML at a required level if they want to build cutting-edge data-centric solutions and products. This book was written to fill a gap that was missing from artificial intelligence literature.
It was also designed to help practitioners interested in a business perspective around artificial intelligence. It gives them the important models they can easily use to better clarify artificial intelligence concepts to their corporation's management team that many people consider hard to learn.
This book will help people who are unfamiliar with AI become more familiar with it and make it seem less complex. It highlights how to identify the many benefits and opportunities that come with it. One of the main focuses is on the reader being able to develop and carry out an effective artificial intelligence tactic and approach, too.
Artificial intelligence is known for being extremely difficult to try and simplify because the nature of it isn't plain and simple. For those who want to learn all there is to know about AI, including things like linear algebra and statistics, vector calculus and matrix, it's the ideal read.
Learning this is easily achievable, but knowing all this complex information isn't always necessary. The book was designed to make difficult things sound less complicated and benefit leaders like managers and executives. Click here to visit Amazon if you're interested in purchasing this book.
You Look Like a Thing, and I Love You: How Artificial Intelligence Works and Why it's Making the World a Weirder Place by Jenelle Shane
This book puts things into perspective where we currently are with artificial intelligence. Humans are currently in a blossoming era of AI applications, but understanding what this all means is extremely important, too, like where it's best used and where it isn't. Regarding the evolution of AI technology, this book reflects where it is right now and makes the tech seem more real.
She has the ability to make artificial intelligence relatable in a unique way. People often think of this technology as a mysterious entity that's much wiser than us when, in fact, it isn't. It makes people feel more comfortable with the technology and something to be less afraid of. It's also a super easy read while fun at the same time. If you'd like to purchase this book you can click here to visit Amazon.com.
