Neural Networks: Difference between revisions
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=Individual Neuron= | =Individual Neuron= | ||
Individual neurons are computational units that read input features, represented as | |||
[[Image:Neuron.png]] | [[Image:Neuron.png]] | ||
Revision as of 02:29, 4 January 2018
Internal
Individual Neuron
Individual neurons are computational units that read input features, represented as
This is a representation of a logistic unit with a sigmoid (logistic) activation function.
The θ vector represents the model's parameters (model's weights). For a multi-layer neural network, the model parameters are collected in matrices named Θ, which will be describe below.
The bias unit is optional, but when it is provided, it is always 1.
Multi-Layer Neural Network
When the output