Top 21 AI Books you must know

Artificial Intelligence will be the hottest and most in-demand field in 2022; most engineers want to work in AI, Data Science, and Data Analytics. The greatest method to learn is to go through the best and most dependable resources, so here is a selection of the best AI Books.

Best Books on AI

We’ve compiled a list of basic and advanced AI books to assist you to navigate the field.

1. Artificial Intelligence – A Modern Approach (3rd Edition) – By Stuart Russell & Peter Norvig

Many people believe this book on artificial intelligence to be one of the greatest AI books for beginners. It’s less technical and gives a high-level review of the most important AI concepts. This edition updates and expands on the changes and advancements in Artificial Intelligence from the book’s last edition in 2003.

This book examines the most recent advances in AI in the areas of practical speech recognition, machine translation, autonomous cars, and home robotics. It also discusses advancements in fields like probabilistic reasoning, machine learning, and computer vision.

2. Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning – By James V Stone

This book covers key neural network learning algorithms and  comprehensive mathematical evaluations. Hands-on experience with neural networks is provided by online computer applications compiled from open source repositories. It’s a great introduction to the algorithmic engines used in modern artificial intelligence.

The author offers a GitHub repository with Python code examples based on the book’s themes.

One of the book’s most notable features is its comprehensive bibliography of essential books and papers that have aided the advancement of deep learning over time. The book provides a historical view on how deep learning progressed over the years, as well as key publications published along the way. You’ll have a thorough and detailed roadmap for deep learning and the long, often twisting course it’s traveled if you use this book as a guide.

3. Life 3.0 Being Human in the Age of Artificial Intelligence – By Max Tegmark

This AI book by Max Tegmark will undoubtedly entice readers to learn more about Artificial Intelligence. It includes a wide range of topics and elements of AI, such as superintelligence, AI’s physical constraints, machine awareness, and so on. It also addresses the subject of automation as well as societal issues that arise as a result of AI. This book takes readers into the current AI thought process in order to investigate the next phase of human existence.

The author looks at how to profit through automation without putting people out of work, how to ensure that future AI systems work as planned without failing or being hacked, and how to thrive in life with AI without being outsmarted by lethal autonomous machines.

4. Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies – By John D. Kelleher, Brian Mac Namee, Aoife D’Arcy

This AI book includes real applications, working examples, and case studies, as well as all of the principles of machine learning. It provides comprehensive descriptions of key machine learning techniques used in predictive analytics. It’s a thorough overview of the most essential machine learning algorithms for predictive data analytics, with both theoretical and practical applications covered.

The four primary approaches are outlined in layman’s terms, with no technical jargon. Algorithms and mathematical models are used to describe each approach, which is accompanied by extensive work examples. The book is appropriate for persons with a basic understanding of computer science, engineering, and mathematics.

5. Machine Learning for Beginners – By Chris Sebastian

Machine Learning for Beginners is intended for complete beginners, as the title suggests. It traces the evolution of machine learning from its beginnings to where it is now. It explains the importance of huge data in machine learning and how programmers use it to create learning algorithms. AI, neural networks, swarm intelligence, and other concepts are thoroughly presented.

This Artificial Intelligence book uses simple examples to help the reader grasp the complicated math and probability statistics that underpin machine learning. It also includes real-life examples of how machine learning algorithms improve our lives.

6. Machine Learning: The New AI – By Ethem Alpaydin

Machine Learning: The New AI is a brief introduction to machine learning. It outlines the evolution of the field, as well as essential learning methods and examples of applications. It explains how digital technology has progressed from number-crunching machines to mobile devices, setting the stage for today’s machine learning boom.

The artificial intelligence book provides examples of how machine learning is employed in our daily lives and how it has penetrated our lives. It also looks ahead to the future of machine learning, as well as the ethical and legal consequences for data privacy and security. This book will be intriguing and easy to understand for anyone who does not have a background in computer science.

7. Superintelligence: Paths, Dangers, Strategies – By Nick Bostrom

The book, which has been recommended by both Elon Musk and Bill Gates, is about navigating the uncertain landscape of AI. Nick Bostrom, the book’s author, is a Swedish-born philosopher and polymath. The foundation for this gem of a book is laid by his knowledge and experience in computational neuroscience and AI.

Bostrom imagines how we can construct Artificial Intelligence that is far better than what we can foresee, as well as the dangers that this entails. He considers scenarios in which things could go awry and whether superintelligence could eventually supplant humans as the planet’s primary lifeform.

One thing that struck me was the similarity between humans and gorillas. Could it be that if gorillas’ fate is determined more by humans than by them, humans’ fate will be determined more by AI than by our species? Another excellent philosophical work about artificial intelligence that raises more issues than it solves (and that how it should be)

8. Machine Learning for Dummies – By John Paul Mueller and Luca Massaron

Machine Learning for Dummies is an excellent starting point for anyone interested in learning more about machine learning. It covers all of the fundamental principles and theories of machine learning, as well as how they apply in practice. It teaches tech machines how to code in Python and R to execute data analysis and pattern-oriented jobs.

Readers can estimate the value of machine learning from simple activities and patterns, such as internet ads, web searches, fraud detection, and so on. This Artificial Intelligence book, written by two data science specialists, makes machine learning simple to understand and implement for any layperson.

9. Make Your Own Neural Network – By Tariq Rashid

One of the artificial intelligence books that take readers on a step-by-step tour of the mathematics of Neural Networks. It begins with very basic concepts and progresses to a full understanding of how neural networks work. It encourages readers to create their own neural networks using the Python programming language.

The book has three sections. The first section covers the many mathematical concepts that underpin neural networks. The second part is more hands-on, with readers learning Python and being encouraged to create their own neural networks. The final portion provides a fascinating look inside the mind of a neural network. It also explains how to execute the commands on a Raspberry Pi.

10. The Singularity Is Near – By Ray Kurzweil

The bestselling author of How to Create a Mind and The Age of Spiritual Machines, whom Bill Gates calls “the finest person I know at predicting the future of artificial intelligence,” offers a daring and optimistic picture of humanity’s future destiny.

The Wall Street Journal dubbed Ray Kurzweil a “restless genius,” and Bill Gates commended him highly. He is a well-known innovator, thinker, and futurist who is passionate about Artificial Intelligence. In this AI book, he discusses the feature of AI that many of us fear the most: ‘Singularity.’ He spends a lot of time talking about how humans and machines can work together.

11. Artificial Intelligence: A Modern Approach (2nd Edition) – By Stuart Russell & Peter Norvig

If you took Norvig’s course to learn about his teaching method, you will long for it! This is the finest book for A.I. newbies. It also covers a wide range of topics, including the search algorithm, working with logic, and more advanced topics. Make this book your first pick when it comes to AI.

The book focuses on the growth of AI systems over time and the formation of specific important knowledge components. It covers text processing, statistical learning, philosophical foundations, reinforcement learning, robotics, and perception.

Many advanced ideas and non-technical learning content are included in this edition. It’s designed in a flexible framework to encourage a variety of teaching approaches.

12. Artificial Intelligence For Humans – By Jeff Heaton

This AI book will assist you in comprehending the fundamental artificial intelligence algorithms. Dimensionality, distance metrics, clustering, and linear regression are just a few of the algorithms covered. These methods were explained using interesting examples and instances. However, you will need a rudimentary understanding of algebra to grasp this book. Otherwise, learning the equations will take longer.

All algorithms that use real numeric computations that you complete on your own are covered in this book. The reader simply needs a rudimentary understanding of college mathematics and computer programming; anything beyond that is well-explained.

13. Paradigms of Artificial Intelligence Programming – By Peter Norvig

This Artificial Intelligence book will teach you how to develop significant A.I. systems using sophisticated common lisp techniques. It’s all about the practicalities. It also teaches readers how to write and debug reliable practical applications.

Furthermore, it provides a greater comprehension of superior programming styles as well as important AI ideas. Furthermore, if you are serious about your job, you should read this AI book.

14. Artificial Intelligence: A New Synthesis – By Nils J. Nilsson

Neural networks, reasoning, and Bayes networks are among the subjects in this AI book. It also explains them very well.

The author, a top researcher and master expositor present a new and inspiring perspective on the subject. The book takes the reader on a fascinating journey through the field of Artificial Intelligence. It offers the book an evolutionary and unifying theme by covering key AI concepts and making frequent use of explanatory visuals and examples.

I wouldn’t recommend this book to a beginner, though. It is, nonetheless, a must-read for expert users.

15. The Emotion Machine: Commonsense Thinking, Artificial Intelligence and the Future of Human Mind – By Marvin Minsky

Marvin provides an interesting model of how human minds work in this Artificial Intelligence book. By observing many forms of mental activity, he is able to predict the future of the human mind. A book can also help you gain perspective and become aware of the present-to-future transition of A.I.

The book explains why we should not limit our thinking ideas and how thinking may change in the future. It also discusses how our minds work, including how we evolve from simple concepts to more complex ones that encourage us to think about ourselves. Self-awareness or consciousness are terms that many people use to describe it.

16. Artificial Intelligence and Soft Computing: Behavioral and Cognitive Modeling of the Human Brain – By Amit Konar

This book provides both cognitively advanced and accessible knowledge. The information is varied but comprehensive. The text is well-written, practical, and comprehensive.

The text begins with “human cognition’s” behavioral opinion. It focuses on the tools and strategies required for intelligent machine implementation.

The author provides a full description of symbolic logic, classical aspects-search, planning, and machine learning, as well as recent research in these fields.

17. Artificial Intelligence: The Basics – By Kevin Warwick

This book provides a basic representation of several AI views as well as the numerous approaches for implementing them. It looks into the history of AI, where it is now, and where it will be in the future. The book contains fascinating depictions of current AI advancement and mechanical autonomy. It also makes recommendations for further books that provide additional information on a certain topic.

Anyone interested in AI should read this book quickly. It delves into the subject’s essential difficulties and provides the reader with clear knowledge. As the name implies, it focuses on the fundamentals and covers all of the issues that belong under the banner of artificial intelligence without digging too deeply into any of them.

18. AI for People and Business – By Alex Castronounis

It’s becoming increasingly important for business leaders to grasp artificial thinking and AI at a sufficient level in order to extract amazing facts from vast data sets and draw judgments from it. This book is a practical guide for entrepreneurs who want to use machine learning to improve the profitability of their businesses and the personal satisfaction of their employees. This is your playbook if you want to drive development by combining information, innovation, planning, and people to address real-world issues on a project scale.

19. Artificial Intelligence By Example – By Denis Rothman

With the use of real-life events, this book offers a beginning point for understanding how Artificial Intelligence works. You’ll learn about the most advanced machine learning models, how to apply AI to blockchain and IoT, and how to use neural networks to generate emotional quotients in chatbots.

By the end of this book, you’ll have a firm grasp on the foundations of AI and will have completed a number of case studies to aid in the development of a corporate vision. This book will assist you in honing your adaptive thinking skills in order to address real-world AI problems. To get the most out of this book, you’ll need prior experience with Python and statistical skills.

20. Artificial Intelligence and Machine Learning – By Chandra S.S.V

This book is mostly for computer science and engineering undergraduate and postgraduate students. This book bridges the gap between Artificial Intelligence and Machine Learning’s tough situations. It has the most case studies and examples that have been worked out. It encompasses several types of learning, including reinforcement, supervised, unsupervised, and statistical learning, in addition to Artificial Intelligence and Machine Learning. This book is highly valuable for students because it has well-explained algorithms and pseudo-codes for each topic.

21. Artificial Intelligence: An Essential Beginner’s Guide to AI, Machine Learning, Robotics, The Internet of Things, Neural Networks, Deep Learning, Reinforcement Learning, and Our Future – By Neil Wilkins

This book provides an overview of Artificial Intelligence as well as a hypothetical simulation of a living brain within a computer. It covers the following subjects:

• Confluence of Interests
• AI Myths
• Manipulating the Limbic System
• Motivation for Creating AI
• Basic Concepts
• Fighting Against Tech Giants
• Seminal Inventions
• Fear-based Consumerism
• AI and Growth Hacking
• AI and Correcting Fake News
• IoT Ecosystem
• AI and Big Data
• AI and Employment
• Dietary Advice by AI
• AI and The Legal System
• AI and Self-driving Vehicles
• Tech Giants As Rulers of Society
• AI as One World Religion
• AI and Loneliness
• Hacking AI
• AI and Ethics
• AI and Social Credit

Conclusion

So those are some of the artificial intelligence books we recommend as a starting point. Machine Learning, Deep Learning, Computer Vision, Neural Networks, and many other topics fall under the umbrella of Artificial Intelligence. Sostart learning AI from these books to master it.