Machines that can see and analyze, robots that can act instead of humans. A century ago it would have sounded as an overview of a new science-fiction bestseller. However, nowadays it’s not fiction anymore. It’s a reality. Are you the one who wants to go with the times? Are you interested in up-to-date technologies such as computer vision and machine learning? Then, perhaps, our list of the best books on artificial intelligence is the very thing you need.
In this article, we’ve gathered the best books about artificial intelligence. Our list contains the books for both beginners and pros. It offers you textbooks, guides, and tutorials to acquire the knowledge you’re dreaming of.
We’ve included the best books about artificial intelligence in various formats. Here you’ll find the books in PDF as well as paper-bound and audio books. Some of these books are available free of charge, while others are to be purchased. Nevertheless, there’s one thing in common for all of them. Each book in our collection is a unique chance to dive deeper into the amazing world of artificial intelligence.
Best Books on Artificial Intelligence in PDF
Possibly, PDF is one of the most widely-used formats today. Therefore, we decided to start our collection from the best books on artificial intelligence and machine learning available in it.
Artificial Intelligence: A Modern Approach
Author: Stuart Jonathan Russell, Peter Norvig
Length: 1152 pages
“Artificial Intelligence: A Modern Approach” is one of the best books on artificial intelligence for beginners. Nevertheless, it is able to arouse the strong interest of computer professionals, linguists, and cognitive scientists as well. To tell the truth, this textbook can be called real classics. The book is an excellent introduction to the theory and practice of artificial intelligence in modern technology. According to the authors, they “tried to explore the full breadth of the field, which encompasses logic, probability, and continuous mathematics; perception, reasoning, learning, and action; and everything from microelectronic devices to robotic planetary explorers”.
Author: Tom M. Mitchell
Length: 421 pages
“Machine Learning” by Tom M. Mitchell is one of the best books on artificial intelligence and machine learning. It’s a comprehensive textbook for novices. It covers the core topics from the area of machine learning. Probability and statistics, artificial intelligence, and neural networks are all unified in a logical and coherent manner. The book is a nice overview of ML theorems with pseudo code summaries of their algorithms. In addition, the author uses examples and diagrams to help you understand these algorithms easily.
Learning OpenCV 3: Computer Vision in C++ with the OpenCV Library
Author: Adrian Kaebler, Gari Bradski
Length: 396 pages
“Learning OpenCV 3” is one of the best books about artificial intelligence from the creators of the OpenCV library. It takes you on an exciting journey across the expanding field of computer vision. This practical guide is aimed at professionals, students, teachers, and hobbyists. Moreover, it offers descriptions, working coded examples, and explanations of the computer vision tools the OpenCV library contains. Besides, it shows how you can build applications that let computers see and make decisions based on that data. What’s more, hands-on exercises in each chapter help you apply what you’ve learned.
Author: Ian Goodfellow, Yoshua Bengio, Aaron Courville
Length: 802 pages
“Deep Learning” is one of the best books on artificial intelligence written by three experts in the field. Frankly speaking, this book is a real treasure for two categories of readers. Firstly, it’s useful for university students beginning a career in deep learning and artiﬁcial intelligence research. Secondly, it’s helpful for software engineers without a machine learning or statistics background. The book consists of three sections. Section I is dedicated to applied math and machine learning basics. The next section II focuses on deep networks and modern practices. The third part – Section III is all about deep learning research.
Machine Learning for Designers
Author: Patrick Hebron
Length: 79 pages
“Machine Learning for Designers” by Patrick Hebron is one of the best books on artificial intelligence for UI and UX designers. With recent advances in content personalization, natural language processing, image recognition, and behavior prediction ML is no longer the tool only for data scientists. Knowledge of ML technologies can help designers find ways to better engage with and understand their users. Patrick Hebron explains how ML applications can affect the way you design websites, mobile applications, and other software. The best thing is that he uses real-world examples to show this impact in practice.
Best Books on Artificial Intelligence for Audio Learners
It’s not a secret that there are people who perceive information much better by listening. That’s why our collection includes a number of audio books on artificial intelligence. In case you prefer listening to reading, this section is especially for you.
How Smart Machines Think
Author: Sean Gerrish
Narrator: Timothy Andrés Pabon
Length: 9 hours
“How Smart Machines Think” by Sean Gerrish is one of the best books on artificial intelligence for beginners and non-technicians. Kevin Murphy, Senior Staff Research Scientist at Google, called it “an excellent layman’s introduction to contemporary AI and machine learning.” Frankly speaking, it’s not surprising. In his book, Gerrish introduces such concepts as AI, machine learning, and deep learning in simple non-technical words. Moreover, he gives real examples of how AI is deployed.
Machine Learning: The Ultimate Guide to Machine Learning, Neural Networks and Deep Learning for Beginners Who Want to Understand Applications, Artificial Intelligence, Data Mining, Big Data, and More
Author: Herbert Jones
Narrator: Timothy Burke, Sam Slydell
Length: 7 hours and 39 minutes
“The Ultimate Guide to Machine Learning” by Herbert Jones is among audio books on artificial intelligence you’ll definitely enjoy. In fact, it’s not one book. It’s a three-in-one version that contains three comprehensive manuscripts in one audiobook. The book focuses on machine learning, neural networks, and deep learning. It covers a wide range of topics from clear definitions of these concepts up to their usage and future.
Machine Learning with TensorFlow: A Deeper Look at Machine Learning with TensorFlow
Author: Frank Millstein
Narrator: Jon Wilkins
Length: 2 hours and 36 minutes
“Machine Learning with TensorFlow” by Frank Millstein is one more example of the best books on artificial intelligence. Do you know what TensorFlow is? If not, this book is your chance to get acquainted with this powerful open source software library. Due to this guide, you’ll learn how to perform various neural network operations. Besides, you’ll find out how to deal with massive data sets. Finally, you’ll get to know how to build your first machine learning model for data classification.
Human + Machine: Reimagining Work in the Age of AI
Author: Paul R. Daugherty, H. James Wilson
Narrator: Jamie Renell
Length: 5 hours and 55 minutes
“Human + Machine” is not an ordinary textbook on artificial intelligence that just tells about video recognition or video tracking. It’s a helpful guide for the companies that want to be ahead of the competition thanks to using AI. Are you ready to innovate to grow your business fast? Then, this audiobook may be a clue. It is based on the experience of 1,500 organizations that have already succeeded. The book shows six completely new types of hybrid human + machine roles that every company must develop. Besides, it contains a “leader’s guide”. It reveals five crucial principles necessary for becoming an AI-fueled business.
Python Machine Learning: Machine Learning Algorithms for Beginners – Data Management and Analytics for Approaching Deep Learning and Neural Networks from Scratch
Author: Ahmed Ph. Abbasi
Narrator: Cole Waterson
Length 2 hours and 2 minutes
“Python Machine Learning” by Ahmed Ph. Abbasi is one of the most comprehensive and easy step-by-step guides for beginners. As you know, machines can learn. This process is possible by using special algorithms. The author of the book will lead you through everything you need to know about algorithms in machine learning. Consequently, you’ll get the basis for understanding deep learning and neural networks. Moreover, you’ll learn how to write simple beginner-level codes using Python.
Best Books on Artificial Intelligence: Paper-Bound Editions
Though we are living in the age of high technologies, not all of us enjoy reading digital books. Undoubtedly, there are still people who prefer turning real pages to using devices for reading. That’s why we couldn’t but add several paper-bound editions to our collection of the best books on artificial intelligence.
Introduction to Artificial Intelligence: Second, Enlarged Edition
Author: Philip C. Jackson, Jr.
Length: 512 pages
“Introduction to Artificial Intelligence” by Philip C. Jackson is an exhaustive survey of artificial intelligence. Possibly, if you look at the date of the first publication you may think that this book is a bit dated. However, its readers won’t agree with you. According to their reviews, the book is “surprisingly still relevant to the current state of the art”. It touches topics such as predicate-calculus theorem, machine architecture, psychological simulation, automatic programming, novel software techniques, industrial automation, etc. Though the book isn’t overly technical, one should have some background in computer science and mathematics to completely enjoy it.
Deep Learning with Python
Author: Francois Chollet
Length: 384 pages
“Deep Learning with Python” is one more of the best books on artificial intelligence. It is written by Francois Chollet, the author of Keras, a widely used library for deep learning in Python. This book boasts intuitive explanations and lots of practical code examples. First and foremost, it enables you to understand the difference between deep learning and AI. Next, it concentrates on such artificial intelligence problems as image classification, speech recognition, question answering, optical character recognition, etc. What’s more, it gives an in-depth introduction to Keras. The experts in the field say that by the end of this book you’ll have enough knowledge and hands-on skills to apply deep learning in your own projects.
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition
Author: Trevor Hastie, Robert Tibshirani, Jerome Friedman
Length: 745 pages
“The Elements of Statistical Learning” is a wonderful source of information on artificial intelligence. It’s for everyone who wants to understand the concepts of data mining, machine learning, and bioinformatics through a statistical approach. The book covers topics such as neural networks, support vector machines, classification trees and boosting to name just a few. It is well written. Moreover, it has lots of informative graphics on almost every page. Also, you’ll find bibliographic notes and exercises at the end of each chapter. The publishers say that the book is relevant for “anyone interested in the field…as an entry point to the area”.
Artificial Intelligence and Soft Computing: Behavioral and Cognitive Modeling of the Human Brain
Author: Amit Konar
Length: 816 pages
“Artificial Intelligence and Soft Computing” by Amit Konar is among the best books on artificial intelligence worth mentioning. The book focuses on both traditional and modern aspects of AI and soft computing. It introduces an in-depth analysis of the mathematical models and algorithms. Furthermore, it shows their applications in the real world problems of significant complexity. Besides, there are two case studies at the end: one on “criminal investigation” and the other on ‘‘navigational planning of robots”. All 24 chapters are written in a clear language easy to perceive. In fact, the high school algebra and elementary differential calculus are enough to understand it.
Reinforcement Learning: An Introduction
Author: Richard S. Sutton, Andrew G. Barto
Length: 344 pages
“Reinforcement Learning” is an introductory book to a relatively new field of AI. It isn’t overwhelmed with tech terms. However, it requires some mathematical background such as familiarity with the elementary concepts of probability. With its three sections, the book covers both the conceptual foundations of reinforcement learning and its latest developments and applications. The first section focuses on the Markov decision processes. The second one is dedicated to dynamic programming, Monte Carlo methods, and temporal-difference learning. The third section presents a unified view of the solution methods. It incorporates artificial neural networks, eligibility traces, and planning.
Of course, these are only a few of the best books on artificial intelligence. However, they can be a good start for your own collection.
Do you know any other books on the subject that are worth the attention of our readers? Please, feel free to share your thoughts in the comments section below.