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

Questions

  1. Can a human beat a chess engine? (Yes | No)
  2. Humans can estimate decisions better than machines with intuition when it comes to large volumes of data. (Yes | No)
  3. Building a reinforcement learning program with a Q function is a feat in itself. Using the results afterward is useless. (Yes | No)
  4. Supervised learning decision tree functions can be used to verify that the result of the unsupervised learning process will produce reliable, predictable results. (Yes | No)
  5. The results of a reinforcement learning program can be used as input to a scheduling system by providing priorities. (Yes | No)
  6. Can artificial intelligence software think like humans? (Yes | No)