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About Neural Networks
This document provides an introduction and overview of neural networks. It discusses the historical background of neural networks and how they were inspired by biological neurons. It then describes the basic components of artificial neural networks, including different types of activation functions. Examples are provided to demonstrate how artificial neurons operate. The document discusses different types of neural network structures, including feedforward and recurrent networks. It also categorizes neural networks based on their learning algorithms, such as supervised, unsupervised, and reinforcement learning. Finally, it provides a brief overview of the single layer perceptron network and its basic delta rule learning algorithm.
Detailed Information
| Author: | ['tt_aljobory3911'] |
|---|---|
| Publication Year: | 2016 |
| Pages: | 38 |
| Language: | English |
| Format: | |
| Price: | FREE |
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