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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
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22
Index

Improving the Emotional Intelligence Deficiencies of Chatbots

Emotions remain irrational and subjective. AI algorithms never forsake rationality and objectivity. Cognitive dissonance ensues, which complicates the task of producing an efficient chatbot.

In Chapter 14, Preparing the Input of Chatbots with Restricted Boltzmann Machines (RBMs) and Principal Component Analysis (PCA), we built a rational chained algorithm process with an RBM and a PCA approach. From there, we extracted critical objective data on a market segment. From that market segment and its features, we then designed a dialog in Chapter 15, Setting Up a Cognitive NLP UI/CUI Chatbot. The dialog was rational, and we produced a probable choice of services for the user. We did this out of good faith, to make the path from a request to its outcome as short as possible. It was a yes path in which everything went smoothly.

In this chapter, we will confront human nature with unexpected reactions. A no path...

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