parameter
The weights and biases that a model learns during training.
Plain English Explanation
The weights and biases that a model learns during training. For example, in a linear regression model, the parameters consist of the bias (b) and all the weights (w1, w2, and so on) in the following formula:
In contrast, hyperparameters are the values that you (or a hyperparameter tuning service) supply to the model. For example, learning rate is a hyperparameter.
How is it used?
Practitioners refer to parameter when building, training, or evaluating machine learning systems. It appears in research papers, product documentation, and technical discussions about AI capabilities and limitations.