21 BEST Artificial Intelligence Books (2024 Update)

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AI is the science and engineering of making intelligent machines, especially intelligent computer programs. The full form of AI is Artificial Intelligence. Artificial intelligence exists when a machine has a cognitive ability. The benchmark for AI is the human level concerning reasoning, speech, and vision.

Are you interested in learning the Artificial Intelligence skills and looking for some excellent book that will help you skyrocket your AI expertise? Then you have come to the right place.

Here is a curated list of the best books to learn Artificial Intelligence for beginners. These books are highly recommended by AI experts and are helpful for students to grasp the programming fundamentals. These resources will guide you to build your career in this promising field and make you a better AI developer.

Best AI Books for Beginners to Expert

Book Title Author Name Latest Edition Publisher Ratings Link
Make Your Own Neural Network Tariq Rashid 1st edition Independently Published Learn More
Artificial Intelligence For Dummies John Paul Mueller 1st edition ‎For Dummies Learn More
Machine Learning For Absolute Beginners O Theobald 2nd edition Scatterplot Press Learn More
Superintelligence Nick Bostrom Unabridged edition ‎Audible Studios on Brilliance audio Learn More
Artificial Intelligence Stuart Russell 3rd edition Pearson Learn More

1) Make Your Own Neural Network

#1 Top Pick
Make Your Own Neural Network

Author Name: Tariq Rashid

Publisher: Pearson Independently Published

Latest Edition: 1st edition

No of Pages: 222 pages

This Artificial Intelligence reference book is a step-by-step journey through the mathematics of neural networks and making your own using the Python computer language.

This reference book takes you on a fun and unhurried journey. The book starts with very simple ideas, and gradually building up an understanding of how neural networks work. In this book, you will also learn to code in Python and make your neural network to offering professionally developed networks.

2) Artificial Intelligence For Dummies

Artificial Intelligence For Dummies

Author Name: John Paul Mueller

Publisher: For Dummies

Latest Edition: 1st edition

No of Pages: 336 pages

Artificial Intelligence is a book written by John Paul Mueller and Luca Massaron. The book provides a clear introduction to AI and how it’s being used today.

Inside this book, you will get an overview of the technology. It also talks about the common misconceptions surrounding it. The book explores the use of AI in computer applications, scope, and history of AI.

3) Machine Learning For Absolute Beginners

Machine Learning For Absolute Beginners

Author Name: O Theobald

Publisher: Scatterplot Press

Latest Edition: 2nd edition

No of Pages: 164 pages

Machine Learning For Absolute Beginners is a book written by Oliver Theobald. The book covers chapters like What is machine learning, types of machine learning, the machine learning toolbox, data scrubbing setting up your data, regression analysis. The book also covers clustering, support vector machines, artificial neural networks, Building a model in Python, etc. It includes algorithms like Cross-Validation, Ensemble Modelling, Grid Search, Feature Engineering, and One-hot Encoding.

4) Superintelligence


Author Name: Nick Bostrom

Publisher: Audible Studios on Brilliance audio

Latest Edition: Unabridged edition

No of Pages: 431 pages

Superintelligence is an ideal reference book written by Stuart Russell and Peter Norvig. This book is the most comprehensive, up-to-date introduction to the theory and practice of the AI subject.

This AI book brings readers up to date on the latest technologies, presents concepts in a more unified manner. The book also offers machine learning, deep learning, transfer learning multi-agent systems, robotics, etc.

5) Artificial Intelligence: A Modern Approach

Artificial Intelligence

Author Name: Stuart Russell

Publisher: Pearson

Latest Edition: 3rd edition

No of Pages: 1152 pages

This book offers a basic conceptual theory of artificial intelligence. It acts as complete reference material for beginners. It helps students in undergraduate or graduate-level courses in Artificial Intelligence.

This edition gives you detailed information about the changes that have taken place in the field of artificial intelligence from its last edition. There are many important applications of AI technology like deployment of practical speech recognition, machine translation, household robotic that are explained in detailed.

6) Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning

Artificial Intelligence Engines

Author Name: James V Stone

Publisher: Sebtel Press

Latest Edition: 1st edition

No of Pages: 218 pages

Artificial Intelligence Engines is a book written by James V Stone. The book explains how AI algorithms, in the form of deep neural networks. It is rapidly eliminating that advantage. Deep neural networks use for many business applications like a cancer diagnosis, object recognition, speech recognition, robotic control, chess, poker, etc.

In this book, key neural network learning algorithms are explained, followed by detailed mathematical analyses.

7) Life 3.0: Being Human in the Age of Artificial Intelligence

Life 3.0

Author Name: Max Tegmark

Publisher: Knopf

Latest Edition: 1st edition

No of Pages: 384 pages

Life 3.0: Being Human in the Age of Artificial Intelligence is a book written by Max Tegmark. The book talks about the rise of AI how it has the potential to transform our future more than any other technology.

This book also cover full range of viewpoints or the most controversial issues. It talks about the meaning, consciousness, and the ultimate physical limits on life in the cosmos.

8) Deep Learning Illustrated

Deep Learning Illustrated

Author Name: Jon Krohn

Publisher: Addison-Wesley Professional

Latest Edition: 1st edition

No of Pages: 416 pages

Deep Learning Illustrated is an AI book written by Jon Kohn, Grant Beyleveld, and Aglae Basens. This book talks about many powerful new artificial intelligence capabilities and algorithm performance. Deep Learning Illustrated and offers a complete introduction to the discipline’s techniques.

This book can serve as a practical reference guide for developers, researchers, analysts, and students who want to apply it.

9) Predictive Analytics For Dummies

Predictive Analytics For Dummies

Author Name: Anasse Bari

Publisher: For Dummies

Latest Edition: 2nd edition

No of Pages: 435 pages

Predictive Analytics For Dummies is a book written by Anasse Bari, Mohamed Chaouchi, and Tommy Jung. With the help of this reference book, you will learn about the core of predictive analytics.

The book offers some common use cases to help you get started. It also covers details on modeling, k-means clustering. The book also provides tips on business goals and approaches.

10) Data Science from Scratch: First Principles with Python

Data Science from Scratch

Author Name: Joel Grus

Publisher: O′Reilly

Latest Edition: 2nd edition

No of Pages: 500 pages

Data Science from Scratch is a book written by Joel Gurus. This book helps you to learn math and statistics that is at the core of data science. You will also learn hacking skills you need to get started as a data scientist.

The books include topics like implement k-nearest neighbors, naïve bayes, linear and logistic regression, decision trees, and clustering models. You will also able to explore natural language processing, network analysis, etc.

11) Hands-On Machine Learning

Hands-On Machine Learning

Author Name: Aurelien Geron

Publisher: Shroff/O'Reilly

Latest Edition: 2nd edition

No of Pages: 848 pages

Hands-On Machine Learning is a book written by Aurélien Géron. The book helps you gain an intuitive understanding of the concepts and tools for building intelligent systems.

This reference material also teaches you techniques, starting with simple linear regression and progressing to deep neural networks. In this book, you will also explore several training models, including support vector machines, decision trees, random forests, and ensemble methods. You can also learn techniques for training and scaling deep neural networks.

12) Applied Artificial Intelligence: A Handbook For Business Leaders

Applied Artificial Intelligence

Author Name: Mariya Yao

Publisher: TOPBOTS

Latest Edition: 1st edition

No of Pages: 246 pages

Applied Artificial Intelligence is a book written by Mariya Yao, Adelyn Zhou, and Marlene Jia. This book is a practical guide for business leaders who are passionate about leveraging machine intelligence. This helps you to enhance the productivity of their organizations and the incase the quality of life in their communities. The book also helps you to take business decisions through applications of AI and machine learning.

13) Prediction Machines: The Simple Economics of Artificial Intelligence

Prediction Machines

Author Name: Ajay Agrawal

Publisher: Harvard Business Review Press

Latest Edition: 1st edition

No of Pages: 250 pages

Prediction Machines is a book written by Ajay Agrawal, Joshua Gans, and Avi Goldfarb. The book talks about the heart of making decisions under uncertainty. It also explains how prediction tools increase productivity– operating machines, handling documents, communicating with customers. In the end, the book discusses how better prediction creates opportunities for new business structures.

14) Human + Machine: Reimagining Work in the Age of AI

Human + Machine

Author Name: Paul R. Daugherty

Publisher: Harvard Business Review Press

Latest Edition: 1st edition

No of Pages: 246 pages

Human + Machine: Reimagining Work in the Age of AI is a book written by Paul R. Daugherty and H. James Wilson. The book talks about the essence of the AI paradigm, which helps you to shift is the transformation of all business processes inside a single organization.

The book explains how companies are using the new rules of AI to leap ahead on innovation. It also describes six entirely new types of hybrid human + machine roles that every company must develop.

15) Architects of Intelligence: The truth about AI from the people building it

Architects of Intelligence

Author Name: Martin Ford

Publisher: Packt Publishing

Latest Edition: 1st edition

No of Pages: 554 pages

Architects of Intelligence contain a series of in-depth, one-to-one interviews where the author, Martin Ford, reveals the truth behind these questions. He has given thoughts of the brightest minds in the Artificial Intelligence community.

This AI book helps collects the opinions of the luminaries of the AI business, Like Stuart Russell, Rodney Brooks, Demis Hassabis, and Yoshua Bengi. You should read this book to get in-depth knowledge and the future of the AI field.

16) Artificial Intelligence for Humans: Fundamental Algorithms

Artificial Intelligence for Humans

Author Name: Jeff Heaton

Publisher: Independently Published

Latest Edition: 1st edition

No of Pages: 224 pages

Artificial Intelligence for Humans is a book written by Jeff Heaton. In this AI book, you will learn about the basic Artificial Intelligence algorithms. Like dimensionality, clustering, error calculation, hill climbing, Nelder Mead, and linear regression.

This Artificial Intelligence book explains all algorithms using actual numeric calculations that you can perform yourself. Every chapter in this book includes a programming example. Examples are currently provided in Java, C#, Python, and C. Other languages planned.

17) HBR’s 10 Must Reads on AI, Analytics, and the New Machine Age

HBR's 10 Must Reads on AI

Author Name: Harvard Business Review

Publisher: Independently Published

Latest Edition: 1st edition

No of Pages: 161 pages

HBR’s 10 Must Reads on AI, Analytics, and the New Machine Age is a book written by Micheal E. Porter, Thomas H. Davenport, Paul Daugherty, H. James Wilson.

The book combed through hundreds of Harvard Business Review articles and selected the most important ones. This book helps you to understand various AI consent and how to adopt them.

In this book, you will learn data science, driven by artificial intelligence and machine learning. It also covers chapters about the blockchain and Augmented reality.

18) TensorFlow in 1 Day: Make your own Neural Network

TensorFlow in 1 Day

Author Name: Krishna Rungta

Publisher: Guru99

Latest Edition: 1st edition

No of Pages: 446 pages

TensorFlow is the most popular Deep Learning Library available in the market. It has a most authentic graph computations feature which helps you to visualize and designed neural network. This useful Machine learning book offers both convolutions as well as Recurrent Neural network.

Machine learning models supported by TensorFlow like Deep Learning Classification, Boston Tree, and wipe & deep layer methods are covered in the book. The book includes complete professional deep learnings practices with detailed examples.

19) Deep Learning (Adaptive Computation and Machine Learning series)

Deep Learning

Author Name: Ian Goodfellow

Publisher: The MIT Press

Latest Edition: 1st edition

No of Pages: 800 pages

This deep learning book offers a mathematical and conceptual background, and relevant concepts in linear algebra, probability and information theory, and machine learning.

The book describes many important deep learning techniques widely used in industry, which includes regularization, optimization algorithms, sequence modeling. This book also offers research-related information like linear factor models, autoencoders, structured probabilistic models, the partition function, etc.

20) Python Machine Learning, 1st Edition

Python Machine Learning

Author Name: Sebastian Raschka

Publisher: Ingram short title

Latest Edition: 1st edition

No of Pages: 454 pages

Python Machine Learning book gives you access to the world of predictive analytics. It helps you to learn the best practices and methods to improve and optimize machine learning systems and algorithms.

Wants to find out how to use Python? Then you should pick up Python Machine Learning. The book helps you to get started from scratch, or helps you to extend your data science knowledge.

21) Deep Learning with R

Deep Learning with R

Author Name: Francois Chollet

Publisher: Manning

Latest Edition: 1st edition

No of Pages: 360 pages

Deep Learning with R introduces you to a universe of deep learning using the Keras library and its R language interface. It is written for Python as Deep Learning with Python by Keras creator and Google.

The books help you set up your deep-learning environment. You can also practice your new skills with R-based applications in computer vision, natural language processing, and generative models. Moreover, to learn this course, you don’t need any previous experience of machine learning or deep learning.


📚 Which book is best for learning Artificial Intelligence (AI)?

Following are some of the best Artificial Intelligence Books for beginners to experts:

🏅 Why Learn Artificial Intelligence?

There are many benefits to learning AI, including:

  • Increased efficiency and productivity.
  • Improved safety and security.
  • Able to increase the ability to process large amounts of data.
  • It helps you to create new products and services.
  • It can help you create more personalized customer experiences.
  • You can create more accurate models and predictions.

🚀 Who can learn Artificial Intelligence?

Anyone can learn Artificial Intelligence, and it is not a specific skill set that you need to have to learn AI.