- Neural Network Programming with TensorFlow
- Manpreet Singh Ghotra Rajdeep Dua
- 278字
- 2021-07-02 15:17:11
Defining feedforward networks
Deep feedforward networks, also called feedforward neural networks, are sometimes also referred to as Multilayer Perceptrons (MLPs). The goal of a feedforward network is to approximate the function of f?. For example, for a classi?er, y=f?(x) maps an input x to a label y. A feedforward network defines a mapping from input to label y=f(x;θ). It learns the value of the parameter θ that results in the best function approximation.
We discuss RNNs in Chapter 5, Recurrent Neural Networks. Feedforward networks are a conceptual stepping stone on the path to recurrent networks, which power many natural language applications. Feedforward neural networks are called networks because they compose together many di?erent functions which represent them. These functions are composed in a directed acyclic graph.
The model is associated with a directed acyclic graph describing how the functions are composed together. For example, there are three functions f(1), f(2), and f(3) connected to form f(x) =f(3)(f(2)(f(1)(x))). These chain structures are the most commonly used structures of neural networks. In this case, f(1) is called the first layer of the network, f(2) is called the second layer, and so on. The overall length of the chain gives the depth of the model. It is from this terminology that the name deep learning arises. The final layer of a feedforward network is called the output layer.

These networks are called neural because they are inspired by neuroscience. Each hidden layer is a vector. The dimensionality of these hidden layers determines the width of the model.
- GitHub Essentials
- 云計算與大數(shù)據(jù)應用
- 數(shù)據(jù)化網(wǎng)站運營深度剖析
- 達夢數(shù)據(jù)庫性能優(yōu)化
- 數(shù)據(jù)革命:大數(shù)據(jù)價值實現(xiàn)方法、技術(shù)與案例
- 大話Oracle Grid:云時代的RAC
- 企業(yè)級數(shù)據(jù)與AI項目成功之道
- 從0到1:JavaScript 快速上手
- 計算機應用基礎(chǔ)教程上機指導與習題集(微課版)
- SQL Server 2012數(shù)據(jù)庫管理教程
- 貫通SQL Server 2008數(shù)據(jù)庫系統(tǒng)開發(fā)
- Hands-On System Programming with C++
- 數(shù)據(jù)指標體系:構(gòu)建方法與應用實踐
- 大數(shù)據(jù)技術(shù)體系詳解:原理、架構(gòu)與實踐
- 推薦系統(tǒng)全鏈路設(shè)計:原理解讀與業(yè)務實踐