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About Ch06 Deep Feedforward Networks
The document describes deep feedforward neural networks, also known as multi-layer perceptrons. It discusses how these networks can learn nonlinear transformations through hidden layers in order to represent complex functions. As an example, it shows how a simple feedforward network with one hidden layer can learn the XOR function, which linear models cannot represent. The network introduces a hidden layer that learns feature representations of the input in a transformed space, allowing a linear model to then solve the problem in this new feature space.
Detailed Information
| Author: | ['黃良初'] |
|---|---|
| Publication Year: | 2021 |
| Pages: | 90 |
| Language: | English |
| Format: | |
| Price: | FREE |
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