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In 2021, Artificial Intelligence is the hottest and demanding field; most engineers want to make their career in AI, Data Science & Data Analytics. Going through the best and reliable resources is the best way to learn, So here is the list of the best AI Books.

Artificial Intelligence is the field of study that simulates the processes of human intelligence on computer systems. These processes include the acquisition of information, using them, and approximating conclusions. The research topics in AI include problem-solving, reasoning, planning, natural language, programming, and machine learning. Automation, Robotics and sophisticated computer software and programs characterize a career in Artificial Intelligence. Basic foundations in maths, technology, logic, and engineering can go a long way in kick-starting a career in Artificial Intelligence.

Here we have listed a few basic and advanced Artificial Intelligence books, which will help you find your way around AI.

By Stuart Russell and Peter Norvig

This edition covers the changes and developments in Artificial Intelligence since those covered in the last edition of this book in 2003. This book covers the latest development in AI in the field of practical speech recognition, machine translation, autonomous vehicles, and household robotics. It also covers the progress, in areas such as probabilistic reasoning, machine learning, and computer vision.

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By James V Stone

In this book, key neural network learning algorithms are explained, followed by detailed mathematical analyses. Online computer programs collated from open source repositories give hands-on experience of neural networks. It is an ideal introduction to the algorithmic engines of modern-day artificial intelligence.

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By Denis Rothman

This book serves as a starting point for understanding how Artificial Intelligence works with the help of real-life scenarios. You will be able to understand the most advanced machine learning models, understand how to apply AI to blockchain and IoT, and develop emotional quotient in chatbots using neural networks. By the end of this book, you will have understood the fundamentals of AI and worked through a number of case studies that will help you develop the business vision. This book will help you develop your adaptive thinking to solve real-life AI case. Prior experience with Python and statistical knowledge is essential to make the most out of this book.

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By Chandra S.S.V

This book is primarily intended for undergraduate and postgraduate students of computer science and engineering. This textbook covers the gap between the difficult contexts of Artificial Intelligence and Machine Learning. It provides the most number of case studies and worked-out examples. In addition to Artificial Intelligence and Machine Learning, it also covers various types of learning like reinforced, supervised, unsupervised and statistical learning. It features well-explained algorithms and pseudo-codes for each topic which makes this book very useful for students.

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By Tom Taulli

This book equips you with a fundamental grasp of Artificial Intelligence and its impact. It provides a non-technical introduction to important concepts such as Machine Learning, Deep Learning, Natural Language Processing, Robotics and more. Further the author expands on the questions surrounding the future impact of AI on aspects that include societal trends, ethics, governments, company structures and daily life.

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By Neil Wilkins

This book gives you a glimpse into Artificial Intelligence and a hypothetical simulation of a living brain inside a computer. This book features the following topics:

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By Deepak Khemani

This book follows a bottom-up approach exploring the basic strategies needed problem-solving mainly on the intelligence part. Its main features include an introductory course on Artificial Intelligence, a knowledge-based approach using agents all across and detailed, well-structured algorithms with proofs.

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By Mariya Yao, Adelyn Zhou, Marlene Jia

Applied Artificial Intelligence is a practical guide for business leaders who are passionate about leveraging machine intelligence to enhance the productivity of their organizations and the quality of life in their communities. This book focuses on driving concrete business decisions through applications of artificial intelligence and machine language. It is one of the best practical guide for business leaders looking to get a true value from the adoption of Machine Learning Technology.

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By Mahajan MD, Parag Suresh

This book explores the role of Artificial Intelligence in Healthcare, how it is revolutionizing all aspects of healthcare and guides you through the current state and future applications of AI in healthcare, including those under development. It also discusses the ethical concerns related to the use of AI in healthcare, principles of AI & how it works, the vital role of AI in all major medical specialties, & the role of start-ups and corporate players in AI in healthcare.

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By Max Tegmark

This book takes its readers to the heart of the latest AI thought process to explore the next phase of human existence. The author here explores the burning questions of how to prosper through automation without leaving people jobless, how to ensure that future AI systems work as intended without malfunctioning or getting hacked and how to flourish life with AI without eventually getting outsmarted by lethal autonomous machines.

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By Dr. Dheeraj Mehrotra This book delivers an understanding of Artificial Intelligence and Machine Learning with a better framework of technology.

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By Peter Norvig

This book teaches advanced Common Lisp techniques in the context of building major AI systems. It reconstructs authentic, complex AI programs using state-of-the-art Common Lisp, builds and debugs robust practical programs while demonstrating superior programming style and important AI concepts. It is a useful supplement for general AI courses and an indispensable reference for a professional programmer.

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By Rahul Kumar, Ankit Dixit, Denis Rothman, Amir Ziai, Mathew Lamons

This book helps you to gain real-world contextualization using deep learning problems concerning research and application. Design and implement machine intelligence using real-world AI-based examples. This book offers knowledge in machine learning, deep learning, data analysis, TensorFlow, Python, fundamentals of AI and will be able to apply your skills in real-world projects.

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By Giuseppe Bonaccorso, Armando Fandango, Rajalingappaa Shanmugamani

This book is a complete guide to learning popular machine learning algorithms. You will learn how to extract features from your dataset and perform dimensionality reduction by using Python-based libraries. Then you will be learning the advanced features of Tensorflow and implement different techniques related to object classification, object detection, image segmentation and more. By the end of this book, you will have an in-depth knowledge of Tensorflow and will be the go-to person for solving AI problems.

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By Chris Baker

This book explores the potential consequences of Artificial Intelligence and how it will shape the world in the coming years. It familiarizes how AI aims to aid human cognitive limitations. It covers:

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By John Mueller and Luca Massaron

This offers a much-needed entry point for anyone looking to use machine learning to accomplish practical tasks. This book makes it easy to understand and implement machine learning seamlessly. It explains how

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By Ethem Alpaydin

It is a concise overview of machine learning which underlies applications that include recommendation systems, face recognition, and driverless cars. The author offers a concise overview of the subject for the general reader, describing its evolution, explaining important learning algorithms, and presenting example applications.

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By John D. Kelleher, Brian Mac Namee

It is a comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. Finally, the book considers techniques for evaluating prediction models and offers two case studies that describe specific data analytics projects through each phase of development, from formulating the business problem to implementation of the analytics solution.

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By Chris Sebastian

This book traces the development of Machine Learning from the early days of computer learning to machines being able to beat human experts. It explains the importance of data and how massive amounts of it provide ML programmers with the information they need to developing learning algorithms. This book explores the relationship between Artificial Intelligence and Machine Learning.

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By Deepti Gupta

It is a Data Science Bool with an effective understanding on ML Algorithms on R and SAS. This book provides real-time industrial data sets. It covers the Role of Analytics in various Industries with case studies in Banking, Retail, Telecommunications, Healthcare, Airlines and FMCG along with Analytical Solutions.

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By Lopez de Prado, Marcos

This book teaches readers how to structure Big Data in a way that is amenable to Machine Language Algorithms, how to conduct research on that data with ML algorithms, how to use supercomputing methods and how to backtest discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis and explains scientifically sound solutions using math, supported by code and examples.

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By Stuart Russel

In this book, the author explores the idea of intelligence in humans and machines. He describes the near time benefits that can be expected from intelligent personal assistants to vastly accelerated scientific researches. The author suggests that AI can be built on a new foundation by which machines will be designed where they will be uncertain about the human preference they are required to satisfy. Such machines would be humble, altruistic and committed to pursuing human objectives.

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A career in Artificial Intelligence can be realized in a variety of spheres which include private organizations, public undertakings, education, arts, health care, government services, and military. The extent of artificial intelligence continues to advance every day. Hence, those with the ability to translate those digital bits of data into meaningful human conclusions will be able to sustain a much rewarding career in this field. You can check out a lot many courses and certifications provided online in this field. If your intent is promising, the courses will definitely be promising and a whole lot of opportunities will show up on your way.

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