Artificial intelligence (AI) has been making great progress over the past few years, and the emergence of large language models (LLMS) marks a major milestone in its growth. With such widespread adoption, it is not uncommon for this revolution to be excluded. One way an individual can keep up to date with trends is to read books on every aspect of AI. Here are the top books for AI books to read in 2025.
Deep Learning (Adaptive Computing and Machine Learning Series)
This book covers a wide range of deep learning topics and their mathematical and conceptual backgrounds. It also provides information on different deep learning technologies used in a variety of industrial applications.
Python: Advanced Guide to Artificial Intelligence
This book can help individuals become familiar with the most popular machine learning (ML) algorithms and dig into the details of deep learning, covering topics such as CNN, RNN, and more. It provides a comprehensive understanding of advanced AI concepts while using Python to focus on their actual implementation.
Fake machine learning (in Python and R)
This book explains the basics of machine learning by using Python and R to provide practical examples, which is a beginner’s guide to beginners in the field and a great starting point.
Machine Learning for Beginners
Given the growth rate of machine learning systems, this book provides a good foundation for anyone who has moved to the field. The author talks about the historical context of machine intelligence and provides beginners with information on how advanced algorithms work.
Artificial Intelligence: A Modern Approach
This is a highly acclaimed book covering the breadth of AI topics, including problem solving, knowledge representation, machine learning, and natural language processing. It provides theoretical explanations as well as practical examples, which is an excellent starting point for anyone looking to sneak into the AI world.
Human Compatibility: Artificial Intelligence and Control Issues
The book discusses the inevitable conflict between humans and machines, providing important context before we advocate for AI. The author also discusses the possibilities of superhuman AI and questions the concepts of human understanding and machine learning.
Consistency Questions: Machine Learning and Human Values
This book talks about a concept called “Aligning Problem” that we aim to teach, systems that do not proceed as expected and various moral and existential risks arise.
Life 3.0: Becoming a Human in the Age of Artificial Intelligence
The author of the book talks about issues such as the future of AI and the possibility of Superman Intelligence becoming our master. He also talked about how we ensure that these systems execute without failure.
The coming wave: technology, power and the biggest dilemma of the twenty-first century
The book warns of the risks posed by emerging technologies to the global order. It covers topics such as robotics and large language models and examines the power that drives these innovations.
Artificial Intelligence Engine: Introduction to the tutorial on deep learning mathematics
The “Artificial Intelligence Engine” conducts in-depth research on the mathematical foundations of deep learning. It provides a holistic understanding of deep learning, covering the historical development of neural networks as well as modern technology and architecture, while focusing on basic mathematical concepts.
Neural Networks and Deep Learning
This book covers the basic concepts of neural networks and deep learning. It also covers the same mathematical aspects, covering topics such as linear algebra, probability theory and numerical calculations.
Human artificial intelligence
This book explains how to use AI algorithms using actual digital calculations. The book is designed to target people without a broad mathematical background, with examples of different programming languages following each unit.
AI superpowers: China, Silicon Valley and the New World Order
The author of this book explains the unexpected consequences of AI development. The book illustrates the competition between the United States and China in AI innovation through practical activities.
Hello World: Becoming a Human in the Age of Algorithms
The author discusses the functions and limitations of algorithms widely used today. The book prepares readers for the moral uncertainty of the world run by code.
Master Algorithm: How the pursuit of the ultimate learning machine will remake our world
This book discusses the concept of a “main algorithm”, an overarching learning algorithm that combines different methods.
Applied Artificial Intelligence: A Handbook for Business Leaders
“Applied Artificial Intelligence” provides enterprises with guidance on how to leverage AI to drive innovation and growth. It covers various applications of AI and also explores its ethical considerations. Furthermore, it sheds light on building AI teams and talent mastery.
Super Intelligence: Path, Danger, Strategy
This book raises questions like whether AI agents will save or destroy us, and what happens when machines surpass people in general intelligence. The author talks about the importance of global cooperation in developing secure AI.
We make little profit from the purchases we buy Recommended/affiliated links attached to each book mentioned in the list above.
If you would like to suggest any books we missed from this list, please email us [email protected]
Shobha is a data analyst with a strong track record of developing innovative machine learning solutions to drive business value.
