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Deep Learning For Dummies
book

Deep Learning For Dummies

by John Paul Mueller, Luca Massaron
May 2019
Intermediate to advanced content levelIntermediate to advanced
368 pages
9h 55m
English
For Dummies
Content preview from Deep Learning For Dummies

Chapter 8

Building a Basic Neural Network

IN THIS CHAPTER

Bullet Considering the basic architecture

Bullet Defining the problem

Bullet Understanding the solution process

Chapter 7 introduces neural networks using the simplest and most basic neural network of all: the perceptron. However, neural networks come in a number of forms, each of which has advantages. Fortunately, all the forms of neural networks follow a basic architecture and rely on certain strategies to accomplish what they need to do. If you learn how a basic neural network works, you can figure out how more complex architectures operate. The first part of this chapter discusses the basics of neural network functionality — that is, what you need to know to understand how a neural network performs useful work. It explains neural network functionality using a basic neural network that you can build from scratch using Python.

The second part of the chapter delves into some differences between neural networks. For example, you discover in Chapter 7 that individual neurons fire after reaching a particular threshold. An activation function determines when the input is sufficient for the neuron to fire, so knowing which activator functions are ...

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ISBN: 9781119543046Purchase book