AI engineering glossary · Classical ML algorithms
What is sigmoid function?
Sigmoid function (also called Logistic function): The S-shaped function sigma(z) = 1 / (1 + e^-z) that maps any real number to a value between 0 and 1. It turns a raw score into something readable as a probability. It is smooth, so its slope can be used for training, but it flattens for large positive or negative inputs.
Sigmoid function: an example
sigma(0) = 0.5, sigma(4) is about 0.982, and sigma(-4) is about 0.018.
Related terms
More Classical ML algorithms terms
- Silhouette score
- Simple linear regression
- Soft margin
- Softmax regression
- Spectral clustering
- Stacking
- Support
- Support vector
Where you learn it
Sigmoid function is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.