Artificial Intelligence (AI) has been making significant strides over the past few years, with the emergence of Large Language Models (LLMs) marking a major milestone in its growth. With such widespread adoption, feeling left out of this revolution is not uncommon. One way an individual can stay updated with the latest trends is by reading books on various facets of AI. Following are the top AI books one should read in 2024.Deep Learning (Adaptive Computation and Machine Learning series)This book covers a wide range of deep learning topics along with their mathematical and conceptual background. It also provides information on the different deep learning techniques used in various industrial applications.Python: Advanced Guide to Artificial IntelligenceThis book helps individuals familiarize themselves with the most popular machine learning (ML) algorithms and delves into the details of deep learning, covering topics like CNN, RNN, etc. It provides a comprehensive understanding of advanced AI concepts while focusing on their practical implementation using Python.Machine Learning (in Python and R) for DummiesThis book explains the fundamentals of machine learning by providing practical examples using Python and R. It is a beginner-friendly guide and a good starting point for people new to this field.Machine Learning for BeginnersGiven the pace with which machine learning systems are growing, this book provides a good base for anyone shifting to this field. The author talks about machine intelligences historical background and provides beginners with information on how advanced algorithms work.Artificial Intelligence: A Modern ApproachThis is a well-acclaimed book that covers the breadth of AI topics, including problem-solving, knowledge representation, machine learning, and natural language processing. It provides theoretical explanations along with practical examples, making it an excellent starting point for anyone looking to dive into the world of AI.Human Compatible: Artificial Intelligence and the Problem of ControlThe book discusses the inevitable conflict between humans and machines, providing important context before we advocate for AI. The author also talks about the possibility of superhuman AI and questions the concepts of human comprehension and machine learning.The Alignment Problem: Machine Learning and Human ValuesThis book talks about a concept called The Alignment Problem, where the systems we aim to teach, dont perform as expected, and various ethical and existential risks emerge.Life 3.0: Being Human in the Age of Artificial IntelligenceThe author of this book talks about questions like what the future of AI will look like and the possibility of superhuman intelligence becoming our master. He also talks about how we can ensure these systems perform without malfunctioning.The Coming Wave: Technology, Power, and the Twenty-First Centurys Greatest DilemmaThis book warns about the risks that emerging technologies pose to global order. It covers topics like robotics and large language models and examines the forces that fuel these innovations.Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep LearningArtificial Intelligence Engines dives into the mathematical foundations of deep learning. It provides a holistic understanding of deep learning, covering both the historical development of neural networks as well as modern techniques and architecture while focusing on the underlying mathematical concepts.Neural Networks and Deep LearningThis book covers the fundamental concepts of neural networks and deep learning. It also covers the mathematical aspects of the same, covering topics like linear algebra, probability theory, and numerical computation.Artificial Intelligence for HumansThis book explains how AI algorithms are used using actual numeric calculations. The book aims to target those without an extensive mathematical background and each unit is followed by examples in different programming languages.AI Superpowers: China, Silicon Valley, and the New World OrderThe author of this book explains the unexpected consequences of AI development. The book sheds light on the competition between the USA and China over AI innovations through actual events.Hello World: Being Human in the Age of AlgorithmsThe author talks about the powers and limitations of the algorithms that are widely used today. The book prepares its readers for the moral uncertainties of a world run by code.The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our WorldThis book talks about the concept of the Master algorithm, which is a single, overarching learning algorithm capable of incorporating different approaches.Applied Artificial Intelligence: A Handbook for Business LeadersApplied Artificial Intelligence provides a guide for businesses on how to leverage AI to drive innovation and growth. It covers various applications of AI and also explores its ethical considerations. Additionally, it sheds light on building AI teams and talent acquisition.Superintelligence: Paths, Dangers, StrategiesThis book asks questions like whether AI agents will save or destroy us and what happens when machines surpass humans in general intelligence. The author talks about the importance of global collaboration in developing safe AI.We make a small profit from purchases made via referral/affiliate links attached to each book mentioned in the above list.If you want to suggest any book that we missed from this list, then please email us atasif@marktechpost.com Shobha Kakkar+ postsShobha is a data analyst with a proven track record of developing innovative machine-learning solutions that drive business value. LinkedIn event, 'One Platform, Multimodal Possibilities,' where Encord CEO Eric Landau and Head of Product Engineering, Justin Sharps will talk how they are reinventing data development process to help teams build game-changing multimodal AI models, fast