\( \mu \)

The symbol, \(\mu\), represents the learning rate. It controls the strength of the update procedure of the model's parameters - \( \htmlClass{sdt-0000000083}{\theta} \). The smaller the learning rate, the slower the training.

It is commonly used in gradient-based learning algorithms, where the learning rate controls the size of the step that parameters are moved by during a single iteration of learning.