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

Chapter 4 – Optimizing Your Solutions with K-Means Clustering

  1. Can a prototype be built with random data in corporate environments? (Yes | No)

    The answer is yes, and no. To start developing a prototype, using random data can help make sure that the basic algorithm works as planned.

    However, once the prototype is advanced, it will be more reliable to use a well-designed dataset. Then, once the training has been accomplished, random data can again help to see how your system behaves in all situations.

  2. Do design matrices contain one example per matrix? (Yes | No)

    The answer is no. A good design matrix contains one example in each row or each column depending on the shape you want it to have. But be careful; a design matrix that contains data that is too efficient might overfit. That means the learning algorithm will be efficient with that data but not adapt to new data. On the other hand, if the dataset contains too many...