- Deep Learning with Keras
- Antonio Gulli Sujit Pal
- 173字
- 2021-07-02 23:58:02
Multilayer perceptron — the first example of a network
In this chapter, we define the first example of a network with multiple linear layers. Historically, perceptron was the name given to a model having one single linear layer, and as a consequence, if it has multiple layers, you would call it multilayer perceptron (MLP). The following image represents a generic neural network with one input layer, one intermediate layer and one output layer.

In the preceding diagram, each node in the first layer receives an input and fires according to the predefined local decision boundaries. Then the output of the first layer is passed to the second layer, the results of which are passed to the final output layer consisting of one single neuron. It is interesting to note that this layered organization vaguely resembles the patterns of human vision we discussed earlier.
The net is dense, meaning that each neuron in a layer is connected to all neurons located in the previous layer and to all the neurons in the following layer.
- Learning SQL Server Reporting Services 2012
- Instant uTorrent
- 硬件產品經理手冊:手把手構建智能硬件產品
- Learning Stencyl 3.x Game Development Beginner's Guide
- 分布式微服務架構:原理與實戰
- VCD、DVD原理與維修
- Spring Cloud微服務架構實戰
- Rapid BeagleBoard Prototyping with MATLAB and Simulink
- 筆記本電腦使用、維護與故障排除從入門到精通(第5版)
- 筆記本電腦維修300問
- 龍芯自主可信計算及應用
- “硬”核:硬件產品成功密碼
- 分布式存儲系統:核心技術、系統實現與Go項目實戰
- 基于S5PV210處理器的嵌入式開發完全攻略
- The Machine Learning Workshop