Artificial Intelligence (AI) has been incorporated by almost every industry across the world in a variety of applications including process automation, predictive analysis, improving customer experience, fraud detection, etc. You can start learning about AI and its concepts by reading these Artificial Intelligence Books that upskill with various Artificial Intelligence Courses.
For today’s topic, we have prepared a curated list of the best books on Artificial Intelligence for beginners. These Artificial Intelligence books are highly recommended by the experts and are helpful for students to learn the programming fundamentals. Let’s check out all the AI books one by one.
What is Artificial Intelligence (AI)?
Artificial Intelligence is the field of studying human intelligence on computer systems. It includes the acquisition of information, its uses, and approximating conclusions. However, the AI research topics include planning, problem-solving, reasoning, natural language, programming, and machine learning for robotics, automation, and sophisticated computer software and programs. Basic foundations in maths, technology, logic, and engineering for going a long way.
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Best Artificial Intelligence Books for Beginners
Here we have listed down a total of 30 AI books for learning basic and advanced Artificial Intelligence. Let’s check them out.
1) Artificial Intelligence – A Modern Approach (3rd Edition) – By Stuart Russell & Peter Norvig
This book on artificial intelligence is considered one of the best AI books for beginners. It gives an overview of the various AI topics and less technical knowledge. All concepts are explained in a simple language that can be easily understood by the learner. Even the book touches on advanced AI topics without going in-depth. Overall, it’s a basic AI book to learn about AI for any individual.
2) Machine Learning for Dummies – By John Paul Mueller and Luca Massaron
Machine Learning for Dummies is an entry-level AI book for any individual to learn Machine Learning. It covers all the basic theories and concepts of machine learning and how they are applicable in the real world. Moreover, it introduces a little coding in R and Python to perform data analysis and pattern-oriented tasks.
3) Make Your Own Neural Network – By Tariq Rashid
One of the best books on artificial intelligence provides a step-by-step knowledge of the mathematics of Neural Networks and gradually builds up its working principles. Even it guides you to get the working codes on a Raspberry Pi.
This book is divided into three parts, first one deals with the various mathematical ideas of the neural networks, whereas the second part covers the Python practical to create neural networks, and the third part gives a peek into the mysterious mind of a neural network.
4) Machine Learning: The New AI – By Ethem Alpaydin
This AI book describes the evolution, explanation, important algorithm, and example applications of machine learning. It explains the evolution of digital technology to create number-crunching machines for mobiles. It also discusses the day-to-day lives of machine learning and the future of machine learning including the ethical and legal implications for data privacy and security.
5) 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 covers all the fundamentals, working examples, practical applications, and case studies of machine learning in detail. Four main approaches are explained with algorithms and mathematical models in a very simple way without any technical examples. The book is easy for those who have basic knowledge of computer science, mathematics, statistics, and engineering.
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6) The Hundred-Page Machine Learning Book – By Andriy Burkov
The Hundred-Page Machine Learning Book by Andriy Burkov is considered the best book on machine learning by many industry experts. It covers from introduction to the fundamentals of machine learning. If you want to get familiar with the mathematics behind machine learning algorithms, this book is perfect.
7) Artificial Intelligence for Humans – By Jeff Heaton
This book provides an overview and understanding of AI algorithms. The readers should have a basic knowledge of computer programming and algebra. It covers linear regression, dimensionality, distance metrics, and clustering in dept.
8) Machine Learning for Beginners – By Chris Sebastian
Machine Learning for Beginners is absolutely for beginners it traces the history of the early days of machine learning and describes how big data is important and how programmers use machine learning to develop learning algorithms. Theories such as AI, swarm intelligence, neural networks, etc. are explained in detail.
9) Artificial Intelligence: The Basics – By Kevin Warwick
This book provides a basic overview of different aspects and the various methods of implementing AI. The book has covered modern AI technology and robotics interestingly. It also gives recommendations for other AI books that have more details. It explores issues at the heart of the subject.
10) Machine Learning for Absolute Beginners: A Plain English Introduction – By Oliver Theobald
One of the few artificial intelligence books explains the various theoretical and practical aspects of machine learning in a very simple way. It uses plain English to provide a clear and accessible explanation of various algorithms for beginners.
11) Superintelligence: Paths, Dangers, Strategies – By Nick Bostrom
This book is recommended by both Elon Musk and Bill Gates. The author has experienced computational neuroscience and AI and the book talks about steering the course and lays the premise for this marvel of a book.
12) Life 3.0 – By Max Tegmark
Life 3.0 by Max Tegmark will surely inspire any individual to dive deeper into the field of Artificial Intelligence. It covers all the aspects of AI, automation, and the larger and societal issues including physical limits of AI, superintelligence, machine consciousness, etc.
13) The Singularity Is Near – By Ray Kurzweil
Ray Kurzweil is the leading inventor, thinker, and futurist, highly praised by Bill Gates and also called ‘Restless Genius’ by the Wall Street Journal. His written book on Artificial Intelligence covers the aspect of AI by ‘Singularity’ and the union of humans and the machine.
14) The Sentiment Machine – By Amir Husain
This book points out the age of Artificial Intelligence as the dawn of a new kind of intellectual diversity and challenges us about societal norms in terms of a ‘good life’ assumption. Amir Husain, being a brilliant computer scientist, guides us to embrace AI in our lives for a better tomorrow.
15) The Society of Mind – By Marvin Minsky
The co-founder of the AI Laboratory at MIT, Marvin Minsky has written several Artificial Intelligence Books, and ‘The Society of Mind’ is one of them. This book portrays the mind as a society of tiny components and explores intelligence in the age of AI.
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16) The Emotion Machine – By Marvin Minsky
In this book, Marvin Minsky presents a fascinating model of how the human mind works and describes emotion as another way of thinking. Following up on the “Society of Mind”, Marvin Minsky also argues that a conscious machine can be built to assist humans with their thinking.
17) Human Compatible – Artificial Intelligence and the Problem of Control – By Stuart Russell
The AI researcher, Stuart Russell explains the near-term benefits of AI and its probable misuse cases in this book. In the age of AI, the journey of humanity is optimistic and empathetic. So, the book covers the need for rebuilding AI on a new foundation.
18) Artificial Intelligence for Dummies – by John Paul Mueller
Artificial Intelligence by John Paul Mueller and Luca Massaron, provides a clear introduction to AI and covers the common misconceptions surrounding it. The book explores the day-to-day use of AI in computer applications, its scope, and its history of AI.
19) Artificial Intelligence Engines – by James V Stone
Artificial Intelligence Engines by James V Stone explains AI algorithms through detailed mathematical analyses in the form of deep neural networks for using cancer diagnosis, object recognition, robotic control, speech recognition, chess, poker, etc.
20) Deep Learning Illustrated – by Jon Krohn
Deep Learning Illustrated book talks about the powerful and new capabilities of AI and its algorithm performance. It also offers a complete introduction to discipline techniques. For developers, researchers, and analysts, it works as a practical reference guide.
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21) Data Science from Scratch – by Joel Grus
Data Science from Scratch helps you to learn the core math and statistics of data science. You can gain hacking skills and also be able to explore network analysis, natural language processing, etc. You can implement k-nearest neighbours, linear and logistic regression, naïve Bayes, decision trees, and clustering models.
22) Hands-On Machine Learning – by Aurelien Geron
This book covers the concepts of tools for building intelligent systems and also teaches you techniques, starting from linear regression to deep neural networks. You can explore several training models, including decision trees, support vector machines, random forests, ensemble methods, and scaling deep neural networks.
23) Applied Artificial Intelligence – by Mariya Yao
This book is a practical guide for passionate people of leveraging machine intelligence. It helps to enhance the productivity of organizations and the quality of life in communities. Moreover, it guides you in taking business decisions via AI and machine learning applications.
24) Human+ Machine – by Paul R. Daugherty
This book covers the essence of the AI paradigm for the transformation of all business processes in a single organization. The book explains the new rules of AI to leap ahead on innovation and describes six entirely new types of hybrid human + machine roles.
25) Architects of Intelligence – by Martin Ford
Architects of Intelligence contain the truth of the brightest minds in the Artificial Intelligence community in a series of in-depth, one-to-one interviews. This AI book helps to collect the opinions of the luminaries of the AI business and get knowledge of the AI field.
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26) HBR’s 10 Must Reads on AI – by Harvard Business Review
This book contains hundreds of Harvard Business Review articles that help you to understand various AI consent. Even you will learn data science, driven by machine learning and artificial intelligence. It also covers the blockchain and Augmented reality.
27) Deep Learning – by Ian Goodfellow
This deep learning book offers a conceptual and mathematical background, with relevant concepts in linear algebra, probability, and machine learning. You will get to know important deep learning techniques like regularization, optimization algorithms, and sequence modelling, widely used in industries.
28) Python Machine Learning – by Sebastian Raschka
Giving you access to the world of predictive analytics, the Python Machine Learning book offers the best practices and methods to optimise and improve machine learning systems and their algorithms. Even this book helps you to get started from scratch, and extend your data science knowledge.
29) Artificial Intelligence and Machine Learning – by Chandra S.S.V
This book is for undergraduate and postgraduate students of computer science and engineering. It covers the gap between the difficult contexts of Machine Learning and Artificial Intelligence. This book contains several case studies, worked-out examples, and various types of learning as supervised, unsupervised, reinforced, and statistical learning.
30) Basics of Artificial Intelligence & Machine Learning – by Dr Dheeraj Mehrotra
This book delivers an understanding of concepts and theories of Artificial Intelligence and Machine Learning with a better framework of technology. The aspect delivers a common understanding of the AI topics concerning its impact on our lives.
So, these are some of the artificial intelligence books, we recommend to start with. There are Machine Learning, Deep Learning, Neural Networks, Computer Vision, and many other concepts under AI, you need to touch upon. However, the reader doesn’t need to have any coding experience or mathematical background to understand these AI books.
I hope you will be helpful with this article, and please share it, so the people who want to learn about AI, will be helpful. You can share your knowledge and thoughts regarding these ai books in the comment section. Also, feel free to ask your queries in the comments. Stay tuned and thanks for reading.!