April 2019
Intermediate to advanced
426 pages
11h 13m
English
Content preview from Mastering Python for Finance - Second Edition
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Activation function
An activation function is part of an artificial neuron that transforms the sum of weighted inputs into another value for the next layer. Usually, the range of this output value is -1 or 0 to 1. An artificial neuron is said to be activated when it passes a non-zero value to another neuron. There are several types of activation functions, mainly:
- Linear
- Sigmoid
- Tanh
- Hard tanh
- Rectified linear unit
- Leaky ReLU
- Softplus
For example, a rectified linear unit (ReLU) function is written as:
The ReLU activates a node with the same input value only when the input is above zero. Researchers prefer to use ReLU as it trains better ...
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