External configuration settings that are not learned from the data but are set prior to the training process.
These parameters influence the overall behavior of a machine learning model, impacting how the model learns and generalizes from the training data.
What is Parameters in AI/ML?
Internal variables that a model learns from the training data.
Values that the machine learning algorithm adjusts during the training process to make predictions on new, unseen data.
During the training process, the model iteratively adjusts its parameters to minimize the difference between its predictions and the actual target values in the training data.
The quality of the learned parameters determines how well the model generalizes to new, unseen data.
After training, these learned parameters are used to make predictions on new input data.
