Top 5 Books for Artificial Intelligence

1. Artificial Intelligence- A Modern Approach

 Artificial Intelligence- A Modern Approach written by J.Russell and Peter Norvig is one of the best book for learning artificial intelligence. This book includes all the basic topics necessary for learning AI like search algorithms, statistical natural language processing, game theory, local search planning methods etc. In addition to this, it also covers the basics of some advanced AI topics.

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2. Make Your Own Neural Networks

 Neural networks are a key element of deep learning and AI and this book by Tariq Rashid perfectly explains the concepts of Neural Networks. The author starts the book with a very basic explanation and simple ideas and gradually builds an understanding of how neural networks work. This book also encourages the readers to build their own neural networks and hence, the name.

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3. Artificial Intelligence Basics

 Artificial Intelligence Basics written by Tom Taulli gives a non-technical introduction to the basic concepts of AI such as NLP, deep learning, robotics and more in an engaging manner. This book comprises of real-world case studies to provide a better understanding of the core concepts like how AI capabilities for robots improve businesses, best practices to successfully implement AI, ethical concerns and other risks of using AI etc.

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4. Introduction to Artificial Intelligence

Introduction to Artificial Intelligence by Philip C Jackson is another top selling book for AI. This book explains the science of reasoning processes in computers and also covers various fields of AI such as game playing, heuristic search theory, robot systems, heuristic scene analysis, specific artificial intelligence accomplishments and much more right from the basics.

Click here to buy Introduction to Artificial Intelligence

 

 

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

 This book written by James V Stone explains the key neural network learning algorithms followed by a detailed mathematical analysis. It includes both historically important neural networks as well as the modern deep neural networks for a better understanding of the both for the reader. The online programs collated from various open source repositories to give hands-on experience of neural networks is another amazing feature of this book.

Click here to buy Artificial Intelligence Engines: A tutorial Introduction to the Mathematics of Deep Learning

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