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

AI as a new frontier

Google has a great, but limited, translation program. Use the flaws to innovate! AI research and development has just scratched the surface of the innovations to come.

First, implement an AI solution. Then, use it for what it is. But don't accept its limits. Don't be negative about it. Innovate! Imagine ideas or listen to other ideas you like and build solutions in a team! Google might even publish your solutions!

Improving Google Translate for any translation is impossible. A realistic approach is to focus on customizing Google Translate for a given domain, such as the transportation company in this example. In the next section, we will focus on ways to customize Google Translate.

Lexical field and polysemy

Google_Translate_Customized.py will provide ideas on how to improve Google Translate in a specific area. This section focuses on the transportation vocabulary error Google Translate made. Once again, Google may rapidly correct...