AI/Machine learning

The terms cost function & loss function are analogous. Loss function: Used when we refer to the error for a single training example. Cost function: Used to refer to an average of the loss functions over an entire training data.

Difference between Model Parameter and Hyperparameter .
Model parameters : are configuration variables that are internal to the model, and a model learns them on its own. For example, W Weights.
Hyperparameters are those parameters that are explicitly defined by the user to control the learning process.
These are usually defined manually by the machine learning engineer. For example , learning rate.

Welcome to our page dedicated to exploring the worlds of machine learning and artificial intelligence , I hope we can help each other.