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
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22
Index

Preparing the Input of Chatbots with Restricted Boltzmann Machines (RBMs) and Principal Component Analysis (PCA)

In the following chapters, we will explore chatbot frameworks and build chatbots. You will find that creating a chatbot structure only takes a few clicks. However, no chatbot can be built without designing the input to prepare the desired dialog flow. The goal of this chapter is to demonstrate how to extract features from a dataset and then use them to gather the basic information to build a chatbot in Chapter 15, Setting up a Cognitive NLP UI/CUI Chatbot.

The input of a dialog requires in-depth research and designing. In this chapter, we will build a restricted Boltzmann machine (RBM) that will analyze a dataset. In Chapter 13, Visualizing Networks with TensorFlow 2.x and TensorBoard, we examined the layers of a convolutional neural network (CNN) and displayed their outputs. This time, we will explore the weights of the RBM. We will go further and use...