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Artificial Intelligence By Example

Artificial Intelligence By Example - Second Edition

By : Denis Rothman
4.6 (17)
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Artificial Intelligence By Example

Artificial Intelligence By Example

4.6 (17)
By: Denis Rothman

Overview of this book

AI has the potential to replicate humans in every field. Artificial Intelligence By Example, Second Edition serves as a starting point for you to understand how AI is built, with the help of intriguing and exciting examples. This book will make you an adaptive thinker and help you apply concepts to real-world scenarios. Using some of the most interesting AI examples, right from computer programs such as a simple chess engine to cognitive chatbots, you will learn how to tackle the machine you are competing with. You will study some of the most advanced machine learning models, understand how to apply AI to blockchain and Internet of Things (IoT), and develop emotional quotient in chatbots using neural networks such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs). This edition also has new examples for hybrid neural networks, combining reinforcement learning (RL) and deep learning (DL), chained algorithms, combining unsupervised learning with decision trees, random forests, combining DL and genetic algorithms, conversational user interfaces (CUI) for chatbots, neuromorphic computing, and quantum computing. By the end of this book, you will understand the fundamentals of AI and have worked through a number of examples that will help you develop your AI solutions.
Table of Contents (23 chapters)
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21
Other Books You May Enjoy
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Index

Quantum Computing

IBM has begun to build quantum computers for research and business purposes. In a few years, quantum computing will become disruptive and will provide exponential computing power. Google, Xanadu, D-Wave, Rigetti, and others devote research budgets to quantum computing.

This unique computer capacity in the history of humanity opens the doors to obtaining results that would be impossible to obtain with classical computers. In 1994, Peter Shor showed that a quantum algorithm could perform better than a classical one for prime factors of an integer and the discrete logarithm problem. Then in 1995, Lov Grover added the unstructured search problem. With the rise of quantum computers, research can go much further.

Quantum computers in themselves will not provide revolutionary algorithms. Any algorithm can be broken down into components that run basic classical machines. Supercomputers can still run artificial intelligence algorithms much easier...

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Artificial Intelligence By Example
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