Beginner · Data
Hyperparameter
Visual diagram · (in preparation) · Math · (in preparation) · Worked example · 3 difficulty levels.
TL;DR. A configuration variable set before the training process begins, controlling aspects of the learning algorithm itself.
Technical Definition
A configuration variable set before the training process begins, controlling aspects of the learning algorithm itself.
How it works
Hyperparameters are external settings that define how a machine learning model is trained, unlike model parameters which are learned during training. Examples include the learning rate or the number of layers in a neural network.
Related Concepts
- Neural Network — A computing system inspired by biological neural networks that learns patterns from data through interconnected layers of nodes.
- Learning Rate — A hyperparameter that controls how large each parameter update step is during gradient descent optimization.
- Machine Learning — A field of AI where systems learn patterns from data instead of following hard-coded rules.