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Hands-On Artificial Intelligence for Beginners

You're reading from   Hands-On Artificial Intelligence for Beginners An introduction to AI concepts, algorithms, and their implementation

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Product type Paperback
Published in Oct 2018
Publisher Packt
ISBN-13 9781788991063
Length 362 pages
Edition 1st Edition
Languages
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Authors (2):
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David Dindi David Dindi
Author Profile Icon David Dindi
David Dindi
Patrick D. Smith Patrick D. Smith
Author Profile Icon Patrick D. Smith
Patrick D. Smith
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Table of Contents (15) Chapters Close

Preface 1. The History of AI 2. Machine Learning Basics FREE CHAPTER 3. Platforms and Other Essentials 4. Your First Artificial Neural Networks 5. Convolutional Neural Networks 6. Recurrent Neural Networks 7. Generative Models 8. Reinforcement Learning 9. Deep Learning for Intelligent Agents 10. Deep Learning for Game Playing 11. Deep Learning for Finance 12. Deep Learning for Robotics 13. Deploying and Maintaining AI Applications 14. Other Books You May Enjoy

Network building blocks

The most basic form of an ANN is known as a feedforward network, sometimes called a multi-layer perceptron. These models, while simplistic in nature, contain the core building blocks for the various types of ANN that we will examine going forward.

In essence, a feedforward neural network is nothing more than a directed graph; there are no loops of recurrent connections between the layers, and information simply flows forward through the graph. Traditionally, when these networks are illustrated, you'll see them represented as in the following diagram:

A feedforward neural network

In this most basic form, ANNs are typically organized into three basic layers; an input layer, a hidden layer, and an output layer, each made up of many basic input/output processing units commonly referred to as neurons. While it's helpful to view networks as basic...

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