Artificial Intelligence (AI) has evolved over time and moved from being just a futuristic concept to becoming an everyday reality. With its help, the human race is gradually being ushered into a new technological era.
If you are an AI fan or enthusiast who desires to learn more about the subject, the following books are the top five reading materials to check. If you prefer visual learning, then check out the infographic provided by TechJury.
Top Five Artificial Intelligence Books to Read
Introduction To Artificial Intelligence By Philip C Jackson
Introduction to Artificial Intelligence was initially printed more than 40 years ago. An updated second edition was published in 1985. This book is regarded as a classic by renowned AI enthusiasts and researchers and provides the perfect introduction to this topic.
It discusses different subjects including psychological simulation, proving a predicate-calculus theorem, novel software techniques, machine architecture, industrial automation, and automatic programming.
More light has been thrown on these themes with clear illustrations and diagrams to enhance the understanding of the readers. It is a book targeted at those who are just beginning to explore the world of AI and are willing to have a deeper understanding of the niche.
Deep Learning (Adaptive Computation And Machine Learning Series) By Ian Goodfellow, Yoshua Bengio, & Aaron Courville
The authors published this book after about two and a half years of writing. Since the publication in 2016, it has quickly grown to become a comprehensive resource for those interested in the subject of deep learning.
The book was designed to help software engineers and graduate-level university students studying computer science.
The Elements Of Statistical Learning: Data Mining, Inference, And Prediction, Second Edition (Springer Series In Statistics) By Trevor Hastie, Robert Tibshirani & Jerome Friedman
If you are looking to understand the real concepts of machine learning, bioinformatics, and data mining, this is the right book for you.
It deals with the subject through a statistical approach and provides comprehensive information. You will also learn about support vector machines, classification trees, neural networks, and similar.
Python Machine Learning By Sebastian Raschka
Python Machine Learning is a convenient guide to the subject of machine learning. It goes into details about what deep learning is and provides the perfect approach for a better understanding through the most recent developments in predictive analytics.
The book deals with issues such as Pylearn2, Theano, and scikit-learn. It also provides tips and guidance on sentiment analysis and neural networks.
How To Create A Mind: The Secret Of Human Thought Revealed By Ray Kurzweil
How to Create a Mind is authored by Ray Kurzweil, an acclaimed futurist. The subject of future civilizations is intensely discussed in this book, as well as how humans and machines are interconnected.
Kurzweil describes how reverse engineering implemented on the human brain could lead to the rise and development of intelligent machines. The subject is tackled through clear explanations, and the book is perfect for people interested in the future of advanced machine learning.
It also discusses the relationship between humanity and intelligent machines, with specific themes like the quantification of uncertainty, logical agents, communication, natural language processing, perception, and a lot more.
All the above-listed books are well known in the Artificial Intelligence (AI) niche, and you will most likely find them easily in all major bookstores worldwide.
Emmy Skylar started working for Debate Report in 2017. Emmy grew up in a small town in northern Manitoba. But moved to Ontario for university. Before joining Debate Report, Emmy briefly worked as a freelance journalist for CBC News. She covers politics and the economy.