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Activation Functions
Calculate and visualize neural network activation functions (Sigmoid, tanh, ReLU, etc.).
| Function | Value | Derivative |
|---|
Jak używać
Enter a value of x and the tool evaluates the common neural-network activation functions — Sigmoid, tanh, ReLU, Leaky ReLU, Softplus, and ELU — showing each function's output and its derivative at that point. Seeing values and gradients side by side makes it easy to build intuition for saturation and vanishing-gradient behavior, or to verify numbers you are using in an implementation.
- Sigmoid
- tanh
- ReLU / Leaky ReLU
- Softplus
- ELU
- Derivative values
Zastosowania
- Machine learning study
- Activation function behavior
- Function and derivative values
- Compare function shapes