Book Image

Artificial Intelligence By Example - Second Edition

By : Denis Rothman
Book Image

Artificial Intelligence By Example - Second Edition

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)
21
Other Books You May Enjoy
22
Index

Summary

This chapter, like the previous chapter, described a connected IoT process with no humans involved. This trend will expand into every field in the years to come.

This also shows that knowing how to use a tool requires hard work, especially when learning artificial intelligence. Imagining a solution for a given market requires more than hard work. Creativity does not come with work. It develops by freeing your mind from any form of constraint.

Once the solution has been imagined, then comes the fine line between developing too much for a presentation and not showing enough. A CRLMM provides the kind of framework that helps build a technical solution (CNN, MDP, SVM, and optimizers) while keeping everyday concepts that others understand in mind.

The chapter also shows that an artificial intelligence model can contain an ensemble of algorithms, RL, DL, SVM, and CRL cognitive approaches, and more.

The next chapter will take us deeper under the...