What are the common parameters used in AI models?

What are the common parameters used in AI models?

Common parameters in AI models include learning rate, batch size, number of epochs, and regularization techniques.

Can you explain what learning rate means?

The learning rate determines how much to change the model in response to the estimated error each time the model weights are updated.

What is batch size and why is it important?

Batch size refers to the number of training examples utilized in one iteration. It affects the stability of the training process.

How do epochs relate to training a model?

An epoch is one complete pass through the entire training dataset. Multiple epochs are often needed to improve model accuracy.

What are regularization techniques?

Regularization techniques are methods used to prevent overfitting by adding a penalty to the loss function.