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10 Best AI (Artificial Intelligence) Books for Beginners in 2021


AI is the science and engineering of making intelligent machines, especially intelligent computer programs. The full form of AI is Artificial Intelligence. Artificial intelligence exists when a machine has a cognitive ability. The benchmark for AI is the human level concerning reasoning, speech, and vision.

Here is a curated list of Top AI Books that should be part of any beginner to advanced Data Science Learner's library.

1) Artificial Intelligence For Dummies

Artificial Intelligence is a book written by John Paul Mueller and Luca Massaron. The book provides a clear introduction to AI and how it's being used today.

Inside this book, you will get an overview of the technology. It also talks about the common misconceptions surrounding it. The book explores the use of AI in computer applications, scope, and history of AI.




2) Make Your Own Neural Network

This Artificial Intelligence reference book is a step-by-step journey through the mathematics of neural networks and making your own using the Python computer language.

This reference book takes you on a fun and unhurried journey. The book starts with very simple ideas, and gradually building up an understanding of how neural networks work. In this book, you will also learn to code in Python and make your neural network to offering professionally developed networks.



3) Superintelligence

Superintelligence is an ideal reference book written by Stuart Russell and Peter Norvig. This book is the most comprehensive, up-to-date introduction to the theory and practice of the AI subject.

This AI book brings readers up to date on the latest technologies, presents concepts in a more unified manner. The book also offers machine learning, deep learning, transfer learning multi-agent systems, robotics, etc.





4) Artificial Intelligence: A Modern Approach

This book offers a basic conceptual theory of artificial intelligence. It acts as complete reference material for beginners. It helps students in undergraduate or graduate-level courses in Artificial Intelligence.

This edition gives you detailed information about the changes that have taken place in the field of artificial intelligence from its last edition. There are many important applications of AI technology like deployment of practical speech recognition, machine translation, household robotic that are explained in detailed.


5) Artificial Intelligence Engines: A Tutorial Introduction to the Mathematics of Deep Learning

Artificial Intelligence Engines is a book written by James V Stone. The book explains how AI algorithms, in the form of deep neural networks. It is rapidly eliminating that advantage. Deep neural networks use for many business applications like a cancer diagnosis, object recognition, speech recognition, robotic control, chess, poker, etc.

In this book, key neural network learning algorithms are explained, followed by detailed mathematical analyses.




6) Life 3.0: Being Human in the Age of Artificial Intelligence

Life 3.0: Being Human in the Age of Artificial Intelligence is a book written by Max Tegmark. The book talks about the rise of AI how it has the potential to transform our future more than any other technology.

This book also cover full range of viewpoints or the most controversial issues. It talks about the meaning, consciousness, and the ultimate physical limits on life in the cosmos.




7) Machine Learning For Absolute Beginners

Machine Learning For Absolute Beginners is a book written by Oliver Theobald. The book covers chapters like What is machine learning, types of machine learning, the machine learning toolbox, data scrubbing setting up your data, regression analysis. The book also covers clustering, support vector machines, artificial neural networks, Building a model in Python, etc. It includes algorithms like Cross-Validation, Ensemble Modelling, Grid Search, Feature Engineering, and One-hot Encoding.




8) Deep Learning Illustrated

Deep Learning Illustrated is an AI book written by Jon Kohn, Grant Beyleveld, and Aglae Basens. This book talks about many powerful new artificial intelligence capabilities and algorithm performance. Deep Learning Illustrated and offers a complete introduction to the discipline's techniques.

This book can serve as a practical reference guide for developers, researchers, analysts, and students who want to apply it.



9) Predictive Analytics For Dummies

Predictive Analytics For Dummies is a book written by Anasse Bari, Mohamed Chaouchi, and Tommy Jung. With the help of this reference book, you will learn about the core of predictive analytics.

The book offers some common use cases to help you get started. It also covers details on modeling, k-means clustering. The book also provides tips on business goals and approaches.



10) Data Science from Scratch: First Principles with Python

Data Science from Scratch is a book written by Joel Gurus. This book helps you to learn math and statistics that is at the core of data science. You will also learn hacking skills you need to get started as a data scientist.

The books include topics like implement k-nearest neighbors, naïve bayes, linear and logistic regression, decision trees, and clustering models. You will also able to explore natural language processing, network analysis, etc.



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