Artificial Intelligence (AI) has emerged as a pivotal field in the realm of technology and science, revolutionizing the way machines replicate human intelligence. From chatbots assisting in customer service to algorithms analyzing medical tests, AI has seamlessly integrated into our lives.
This article delves into the realm of AI literature, presenting a curated list of the best AI books for beginners. These resources are not only informative but also serve as a stepping stone for enthusiasts looking to explore the depths of artificial intelligence.
What is Artificial Intelligence?
In the present generation, we hear more about bots, for example when we are searching on a website we find a chatbot there. Similarly, we got AI Bots to get information, there are bots to read medical tests, etc. Isn’t it amazing that these are usually performed by humans? Machines have taken the role now that we refer to as Artificial Intelligence. Further, speech recognition, computer vision, translation of languages, etc. are also certain applications of artificial intelligence. Knowledge of Artificial Intelligence is a need of the hour as the world is growing with machines.
How does Artificial Intelligence work?
It is not easy for a machine to perform human work or possess human intelligence. It takes a lot of work at the back end. Huge datasets are run for the computer systems to understand the pattern. Various algorithms are involved, which are broadly classified under supervised learning, unsupervised learning, and reinforcement learning. Machine learning and deep learning are subsets that support Artificial Intelligence. To summarize, Artificial Intelligence works by the combination of large amounts of data with fast, iterative processes and intelligent algorithms, allowing the software to learn automatically from patterns or features in the data.
The various programming languages artificial intelligence use include Python, Lisp, Java, C++, R, etc. Among all Python and Java are the most used. However, it depends on the process involved.
Best AI Books For Beginners
As we know, books are unparalleled sources of knowledge, offering consolidated and essential details that enrich our understanding. In this article, we have meticulously curated a list of the finest AI books authored by experts in the field, ensuring a comprehensive and insightful exploration of artificial intelligence for beginners.
1. Artificial Intelligence and Machine Learning by Vinod Chandra S. S and Anand Hareendran S
Artificial Intelligence and Machine Learning by Vinod Chandra S. S was published by PHI Learning in 2014.
This book is highly recommended for Undergraduate and Postgraduate students. This lets the readers understand the difficult areas in artificial intelligence and machine learning. The book begins with an introduction to Artificial Intelligence with a few examples such as the water-jug problem, the knight tour’s problem, etc., and its applications. Further, the book discusses the various heuristic search techniques, game playing, knowledge representation, its structures, reasoning, clustering, and learning. The author(s) clearly explains all the algorithms with supporting case studies. The pictorial representations given for the topics provide with deep understanding.
2. Artificial Intelligence – A Modern Approach by StJohn D. Kelleher, Brian Mac Namee, Aoife D’Arcyuart Russell & Peter Norvig
Artificial Intelligence- A Modern Approach by StJohn D. Kelleher, Brian Mac Namee, Aoife D’Arcyuart Russell & Peter Norvig was published by Pearson. The latest release was the third edition in 2010.
In this book, the authors attempt to explore the full breadth of the field, which encompasses logic, probability, and continuous mathematics; perception, reasoning, learning, and action; and everything from microelectronic devices to robotic planetary explorers. The book begins with an introduction- the foundation and history of artificial intelligence. The problem-solving part deals with various algorithm strategies, beyond classical search, adversarial search concepts, and constraint satisfaction problems. Further, problems, syntax, and semantics of knowledge, reasoning, and planning concepts are discussed. Such concepts include first-order logic, planning graphs, ontological engineering, and so on. Natural Language Processing, Perception, Robotics, and Learning examples are the other areas covered. Thus, it gives an overall understanding of all the Artificial Intelligence Concepts.
3. Make Your Own Neural Network By Tariq Rashid
Make your own Neural Network by Tariq Rashid was published in 2016.
Neural networks are architecture for deep learning from the data which is one of the important parts of artificial intelligence. This book gives a step-by-step explanation of the use of neural networks. Apart from the introduction, the book is split into three parts- How they work, DIY with Python, and Even More Fun. The first is most of the ideas whereas the second one is practical. The third part extends the ideas further. The book deals with using Python programming language to work with neural networks. The book also gives an introduction to calculus and briefs on the usage of Raspberry Pi.
4. Machine Learning: The New AI by Ethem Alpaydin
Machine Learning: The New AI by Ethem Alpaydin was published in 2016 by The MIT Press.
This book provides an overview of machine learning which includes recommendation systems, face recognition, driverless cars, etc. The first chapter deals with the introduction and evolution of digital technology from number-crunching mainframes to desktop personal computers and smart mobile devices. The next chapter is about the basics and applications of machine learning. The author(s) clearly discusses various pattern recognition algorithms. The following chapters cover neural networks, deep learning, segmentation, learning recommendations, reinforcement learning, data science, etc. Thus this book is best suited to getting detailed knowledge of machine learning.
5. Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples and Case Studies by John D. Kelleher, Brian Mac Namee, Aoife D’Arcy
Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples and Case Studies by John D. Kelleher, Brian Mac Namee, and Aoife D’Arcy was published in 2015 by The MIT Press.
This book covers both the theoretical and practical applications of important machine-learning approaches. It describes four approaches to machine learning namely information-based learning, similarity-based learning, probability-based learning, and error-based learning. The book explicitly deals with predictive data analytics applications. Worked examples and case studies are used in the illustration of models. Customer churn, galaxy classification, etc. are such case studies. Further, the book covers the areas of data exploration.
6. Artificial Intelligence For Humans by Jeff Heaton
Artificial Intelligence for Humans by Jeff Heaton was published in 2013.
This is said to be one of the best introductory books. It has in it all the basic artificial intelligence algorithms providing a strong foundation for beginners. Examples are provided in various programming languages such as Java, C#, R, Python, and C. Concepts of random numbers, how it is classified and calculated, the difference between uniform and normal random numbers, K-means clustering, error calculation, the effectiveness of an algorithm calculation, etc. are discussed clearly. The book also introduces simple algorithms that can be trained to analyze data and produce better results. Optimization algorithms, discrete optimization, and linear regressions are other algorithms and problems to take away from the book.
7. Artificial Intelligence: The Basics by Kevin Warwick
Artificial Intelligence: The Basics by Kevin Warwick was published in 2011 by Routledge.
This book provides an illuminating and accessible introduction to Artificial Intelligence. It begins with an introduction to AI providing a gentle helping hand to guide new readers into the subject. The content of the book covers aspects of AI involving philosophy, technology, and basic methods. It also covers various topics in robotics which include artificial life, collective and swarm intelligence, and biologically inspired techniques. It also deals with a new form of AI in the sense of growing biological brains, as the AI, within a physical robot body. Sensing the world has a huge impact on intelligence. The final chapter of the book deals with how sensory input is dealt with in machines.
8. Machine Learning For Beginners By Chris Sebastian
Machine Learning for Beginners by Chris Sebastian was published in 2018.
This book begins with the history of Machine Learning. It describes the relationship between artificial intelligence and machine learning and also the role of neural networks, big data, regression, etc. in machine learning. It compares ML to the Internet Of Things, Robotics, and Swarm Intelligence. Technical problems and philosophical dilemmas with ML are also dealt with in the book. Thus it provides an overall guide on machine learning to beginners.
Conclusion
Hope this article gave you enough detail on what to expect from various books about artificial intelligence. With technology at its peak, knowledge of artificial intelligence would be of greater importance. The above-mentioned are the best AI books for beginners which doesn’t mean they can’t help with the intermediaries and the advanced. It is always a good read for all levels. Take time to learn all the concepts to get a better understanding. But firstly analyze your focus area and learn accordingly.
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FAQs
What are the best AI books for beginners?
The best AI books for beginners are “Artificial Intelligence and Machine Learning” by Vinod Chandra S. S and Anand Hareendran S, “Artificial Intelligence – A Modern Approach” by StJohn D. Kelleher et al., “Make Your Own Neural Network” by Tariq Rashid, and “Machine Learning: The New AI” by Ethem Alpaydin, among others.
How does artificial intelligence work?
Artificial intelligence works by using algorithms and large datasets to enable machines to learn from patterns in data. Machine learning and deep learning are subsets of AI that play a crucial role in this process.
What programming languages are used in artificial intelligence?
Python, Lisp, Java, C++, and R are among the programming languages commonly used in artificial intelligence. Python and Java are particularly popular due to their versatility and robust libraries.
What are the key concepts covered in AI books?
AI books cover a wide range of topics, including heuristic search techniques, game playing, knowledge representation, clustering, learning, natural language processing, robotics, and deep learning.
