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)
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Index

Introducing CNNs

This section describes the basic components of a CNN. CNN_SRATEGY_MODEL.py will illustrate the basic CNN components used to build a model for abstract image detection. For machines, as for humans, concepts are the building blocks of cognition. CNNs constitute one of the pillars of deep learning (multiple layers and neurons).

In this chapter, TensorFlow 2 with Python will be running using Keras libraries that are now part of TensorFlow. If you do not have Python or do not wish to follow the programming exercises, the chapter is self-contained, with graphs and explanations.

Defining a CNN

A convolutional neural network processes information, such as an image, for example, and makes sense out of it.

For example, imagine you have to represent the sun with an ordinary pencil and a piece of paper. It is a sunny day, and the sun is shining very brightly—too brightly. You put on a special pair of very dense sunglasses. Now you can...